6 Tips to Go Beyond Google Analytics for Better Audience Insights


Most of us rely on Google Analytics (GA) for many of our metrics – and for good reason. It’s free and easy to use, and most marketers care more about the statistics from Google over data from the other search engines, i.e. Bing or Yahoo. Yet, while GA does offer a near comprehensive look at your users and how they’re interacting with your site, it can’t tell you everything. And what’s missing may be more important than you realize.

At first I will give you some hints on how you can tweak Google Analytics and use Google Search Console to increase the quality of your trafic. Next, I’m going to tell you about some tools that woill provide you a great deal of valuable information about your customers and prospects. Let’s start!

How to Avoid GA Mistakes You Cannot Fix

If you apply a filter to your account, you can’t in the future simply remove this filter and see the historical data. That data is essentially lost. For example, let’s say that you apply a filter to remove any in-house traffic. If you later want to go back and see the total traffic, you can’t.

One way to avoid this issue is to always create multiple views when you add a filter. You should create a Main/All Website Traffic view, and then create new views for your filters, which can be done in your Admin screen.

Always create the views before adding the filters. Once the filters are added, you can’t go back and undo it.

The Keywords Data Dilemma

We all remember the “Not Provided” scandal of a few years back when Google basically stopped offering search keywords within GA. You can, however, still find this data within Google’s Search Console. Here, you can find search queries (exact keywords someone searched), clicks, impressions, average position and CTR. You can click on each query and see where the user landed. You can also see the landing page of each visit.

You should connect your Google Search Console to your GA account. You will then be able to see the search query information within GA.

User Experience Evaluation

GA can track bounce rate, time on site, conversion rate and more. What it can’t track is how long it takes someone to fill out a form, why they abandoned their cart and how they engage on the site. Google’s Page Analytics plugin will provide what percentage of people clicked where on a site (i.e. 3.9% clicked on the button in the header), but the plugin only provides high-level data about where people are clicking. It will give you some idea as to why they chose to click on the button in the header as opposed to the drop-down menu. This, however, may not be enough for your needs.

You can track how people interact with your forms, and see the detailed heatmaps of your web pages with the help of either multiple tools (you han find a good list from Kissmetrics Blog article) or a single tool (e.g. Mouseflow.) 

Call Tracking

While people have shifted away from picking up the phone and making a call, it still happens, especially for small business and brick-and-mortar shops. Your number is typically listed on your website, direct mail pieces, social networks and more. So, how do you know which marketing campaign is driving the most phone calls? GA can’t track this data.

Marketers, however, can set up call tracking to capture this info. According to the 2016 Call Intelligence Index published by Invoca, 92% of business calls come from digital channels. Further, the Search Engine Journal says that a phone call has a conversion rate of 30-50%. That means that if you’re not tracking this data, you’re losing credit for potential leads and sales.

You can leverage companies like e.g. Call Rail to track and record phone calls, and obtain call analytics.

Customer Feedback

Again, GA can tell you that you have a high bounce rate and that a visitor didn’t finish the check-out process, but it doesn’t tell you what your customers really think about your website and your products. Social media, phone calls, emails and other communications, however, can. All marketers should be capturing their online mentions as well as reviewing customer surveys. These provide a more detailed picture of what your customers are thinking and what issues they are having.

Set up a time to regularly review this data, and look for patterns. If you have consistent feedback that your website times out before the final checkout step, then you know where to investigate for website issues.

Identify Who’s Coming to Your Site

Google has taken a stance to never provide Personally Identifiable Information (PII). This data allows you to figure out exactly who’s visiting your site. This means that GA can provide aggregate data about visitors, but you’ll never know who exactly visited your site and what they did on it.

Products like Leadfeeder however, can capture data about your visitors and send it back to you. For example, you can tell that a VP from a company that you’re targeting actually spent time on your site and looked at XYZ product. As a result, you can leverage this data to better market to this person. This is especially useful for B2B companies that may not have a large number of visitors, but who want to ensure that they’re reaching the correct audience.

In addition, Leadfeeder integrates with Google Analytics, thus you can assess the performance of your AdWords campaigns.


As a free tool, there’s no denying that GA is a great resource for finding information on how your overall campaigns are doing. Where it falls short is in providing you more depth into what types of users are coming to your site, what they’re doing there and where they’re having issues. Supplementing GA will additional tools can greatly improve your overall metrics.

These additional metrics will add more complexity to your reports and showcase the overall effectiveness of your campaigns. You should combine this data into a single marketing report. You might have to initially walk stakeholders through it and fully explain the additional information before they understand its importance.


About Misty Faucheux


Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

Pull data from Facebook Ads, Twitter Ads, Bing Ads and 35+ data sources into Google Data Studio with Supermetrics for Google SheetsSTART THE FREE TRIAL NOW »

How to Make A Google Data Studio Dashboard for Adwords, Facebook, Twitter & Bing Data

DATA STUDIO PAID CHANNEL MIX · 9-MINUTE READ · By Supermetrics on April 18 2017.

How to Make A Google Data Studio Dashboard for Adwords,Facebook,Twitter & Bing Data

In our last post, we showed how to make a Facebook Ads dashboard in Data Studio. We posted it on Supermetrics blog. After 4 hours it got shared by Google and a few hundreds of likes/retweets.

Many of you asked for more. So we decided to keep producing Data Studio templates that you would enjoy. And I’m happy to share the next public fruit of this labor – a Paid Channel Mix template with Adwords, Facebook Ads, Twitter Ads and Bing Ads data.

To briefly recap, by far the Google Sheets connector is the only option for pulling non-Google data, such as Facebook, Twitter and Bing, into Data Studio. With Supermetrics, you can set up a feed of data to be easily imported into Google Data Studio.

In this post I’ll explain how to connect your data feeds from multiple platforms to Google Data Studio.

To learn how to copy this template, jump directly to here.

Decide what your feeds consist of and create a feed for each platform

To get started, let’s say you want a simple overview of top level data for the last 3 years across AdWords, Bing, Twitter, and Facebook.

For this to work, you will need a separate query for each platform. On the sidebar launcher, select a data source. Then, you want to select your date range:

Calculated fields vs. pre-calculated metrics

Next, select your metrics. Performance metrics that are pre-calculated (i.e. cost per click, click through rates, and conversion rates) should be set up as calculated fields in Google Data Studio. This set-up is needed to enable your data to be accurate when you use custom data ranges as the tool can only use AVERAGE, COUNT, COUNT DISTINCT, MAX, MIN and SUM functions for your data ranges.

Setting up calculated fields in Data Studio is fairly straightforward, just make sure you import key fields such as clicks, impressions, cost, and conversions so that you can use them in your equations.

Take full control of your date range

As you may know, Google Data Studio has a neat date range tool that lets you adapt the data to a specific date range (such as in Google Analytics). In order for this to work, we need to set the data import to include a breakdown by date. Make sure you set your number of rows to allow plenty of space for this!

You may also want to add campaigns, ad groups, and even audience variables as a secondary dimension. This will let you view data split by these categories. You can add and remove dimensions in Google Data Studio when completing your graphs. You can also set up a filter in Data Studio to select which dimension value to show data for.

Make sure you tick, ‘Show all time values’ in the options tab. Your timeline graphs will make more sense!

Multi-source report from one sheet

Now begins the arduous simple task of adding in your additional data source queries. You only need to:

    • Add a column to label which platform the data is coming from
    • Give your metrics common labels to allow aggregation. For example, Facebook and AdWords have different names for similar metrics (clicks and link clicks). But if you want these to be treated the same by Data Studio, change the header to read Clicks. Make sure to set your queries to ‘No header row’ so that this isn’t overridden.
  • After leaving space between each platform to allow for changing number of dimensions, set up your query for the additional platform. Make sure your date range and primary dimension (date) remains constant.

And you’re done! You have your data ready to import to Google Data Studio.

Schedule your data refresh for a truly automated report dashboard!

And if you want to see end results from the steps above, check out our Paid Channel Mix template in Data Studio.

Find the data sheet from here:


How to copy this template for your own accounts

Copy the data sheet with Custom Template in the Supermetrics Template Gallery

Copy the URL of the template sheet:


Go to Supermetrics Google Sheets add-on, open Template Gallery, add it as a Custom Template by pasting the copied URL.

Follow instructions to connect the data sheet to the Adwords, Facebook, Twitter and Bing accounts you want to report on.

In the end, click on the blue Insert Template button.

Last but not least, remember to set up scheduled refreshing to always keep your data up to date.

Don’t know how to use Custom Template? Find it out in this previous post.

Copy the Data Studio report

Connect the copied data sheet as the data source

Create calculated fields

After creating data source, there are only four metrics imported from the sheet, clicks, impressions, cost, and conversions.

Let’s add a few more, CTR, CPC, Conversion rate and Cost per conversion.

And remember to change field type of CTR and Conversion rate to Percent.

Then hit on the blue Create Report button on the top right corner.

Connect your charts to calculated fields

Right after these steps, a lot of data will appear to be missing. At this point, you may think the mission has failed.

But no worries, it just takes a few clicks to make your report work.

And the reason behind is that Data Studio can’t link the newly created calculated fields to the original calculated fields in the template despite they share identical names.

Click on a chart, and go to Invalid Metric in the sidebar.

Then select the right calculated field in the Metric Picker

Repeat it for other charts, scorecards and data tables with missing metrics. Eventually you’ll get your own awesome-looking report!

Have ideas for a new template? 

Just let us know – we’re always working on new templates. If you have an idea for new Data Studio Template that can be created with Supermetrics, please feel free to contact us.

If you haven’t installed our Google Sheets add-on yet, get it for free to make sure you won’t miss our future templates.

Happy Analysing!

Pull data from Facebook Ads, Twitter Ads, Bing Ads and 35+ data sources into Google Data Studio with Supermetrics for Google SheetsSTART THE FREE TRIAL NOW »

Google Data Studio: Creating Reports With Calculated Metrics

GOOGLE DATA STUDIO REPORTS · 6-MINUTE READ · By Tina Arnoldi on April 11 2017.

By now, we hope you have become familiar with Data Studio, still in Beta but available to anyone with a Google account. In an earlier post on our blog, you learned how to use Supermetrics for Google Sheets with Data Studio to use data outside of Google, specifically Facebook. In this post, I to show you an advanced feature of Data Studio – using calculated metrics – and provide another example of reporting with a non-Google data source, this time including Twitter data.

Initially, the free version of Data Studio had a five-report limit per account compared to the number of reports allowed on the enterprise version. In February, Google removed that limit to allow unlimited reporting in the free version so you do not have to re-use reporting slots.

The easiest way to get started with Data Studio is to visit the Google Data Studio Gallery and use an existing report template. This way you can drill into the different features in the report to learn how they were created. And once you make a copy and add it to your account, you are able to make edits. The two screenshots below are from the Google Data Studio Gallery.

Also, you can take a look at the reports other companies create to get some design inspiration.

First Steps In Google Data Studio

To create a new report, log into Data Studio with a Google account. You can see the connectors available in the below screen, such as Google Analytics and applicable demo accounts, such as the Google Merchandise Store. Later I will show you how to use Google Sheets to pull in data from Twitter.

Once you are familiar with some of the reports from the gallery, you are ready to start creating reports for data driven decisions in your organization. When you talk to your team about the type of data you want, draw it out first. It can be a simple sketch with pen and paper.

In the start, identify the audience. Is it members of your marketing team who need to drill into detail or executives who are looking for a high-level overview? What is the purpose of your Data Studio report? Is there a clear action or decision to be made by recipients when they receive the report?

As you work on your reports and learn how to use the different fields and formulas available in Data Studio, spend some time in Google’s support documentation to learn about the different options. In this post, I want to introduce you to calculated fields and then show you how to apply that advanced feature using a Twitter data source.

Calculated Fields

Calculated fields allow you to combine and group data into metrics and dimensions and are added to your data source. An example of a calculated metric shown in this video by Google Analytics is Profit Margin. You do this by first creating a field calling Profit. In this example, it is assumed that we have fields in our data source called revenue and a field called expenses so the new Profit field is calculated as Revenue – Expenses. 

After you’ve calculated profit, you can create Profit Margin and set it to be displayed as a percentage value. You can find a good list of equations for main metrics from this blogpost.

The video also shows you how you can create a custom dimension, such as grouping country values in your data source as a new calculated field you can call sales region. This is done with the CASE statement which “lets you add logic-based flow control to a calculated field” and the regular expression match function.  Do not worry if you have not use RegEx (regular expressions) or CASE statements in the past. You can still follow along with this example so you are aware of the capabilities of Data Studio for calculating your own fields.

Supermetrics for Google Sheets and Data Studio

Let’s now look at how you might use Supermetrics for Google Sheets and Google Data Studio to use data outside of Google which will include a calculated field. With this Add-on, you extend the capabilities of what Google offers in Data Studio by using non-Google data sources, such as Twitter. Google Sheets will pull in Twitter data by using the Supermetrics Add-on. From the Data Studio side, Google Sheets is then selected as the data source.

You start in Google Sheets with the Supermetrics Add-on installed. Select the Add-on and choose a Data Source of Twitter data with the fields you want to pull into sheets. In the below example, you can see the Twitter field names on the right and partial results on the left hand side in resulting Google Sheet:

Next, in Data Studio, I create a new Data Source and choose the Google Sheet that has my Twitter data (which in this case is Sheet2).

Next, I create a simple table in Data Studio to display the Twitter fields that are in Google Sheet2.

Once I had the existing Twitter dimensions and metrics in my Data Studio table, I created an additional field to measure popularity, which of course is definitely subjectively. To make this simple, my new calculated field is called Popular and I will measure Twitter popularity by adding the Tweet retweet count to the Tweet like count as seen below in the calculated field.

The below table shows the Tweet retweet count and Tweet like count fields which were automatically pulled from the Google Sheet that had my Twitter data. The third field is one I calculated from this data for a metric of popularity.

This of course is a very simple example of a calculated field, but shows you the capabilities of Data Studio and the ability to extend those capabilities to pull in non-Google data, such as Twitter, with the Supermetrics Add-on.

I am sure there is a lot more to come with Data Studio which you can follow in Google’s Data Studio forum and can learn more from Google’s support files. Supermetrics is planning to release more Google Data Studio Templates, so stay tuned up!

About Tina Arnoldi

???????????????????????????????????? Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn
Pull data from Facebook Ads, Twitter Ads, Bing Ads and 35+ data sources into Google Data Studio with Supermetrics for Google SheetsSTART THE FREE TRIAL NOW »

Three Ways to Power Up Your Google Analytics Data

POWER UP YOUR DATA · 6-MINUTE READ · By Tina Arnoldi on April 3 2017.

Google Analytics is a powerful, free tool for measuring your marketing efforts. But it doesn’t deliver right out of the box. There are options for customization that you as a marketer need to be aware of so the data you report on makes sense for your business. Here are three ways to power up your Google Analytics data with customizations.

Tag Your Campaigns

If your marketing campaigns are not tagged properly, you will negatively impact a number of Google Analytics reports that will misrepresent your data. The Medium, which records data such as organic, referral, and direct, is the one to get right if you want meaningful reports, especially with your email campaigns.

When you send email campaigns, recipients who use a desktop application like Outlook or MacMail will be incorrectly reported in Google Analytics because these applications do not pass referrer data. 

Webmail traffic, such as mail.google.com or outlook.live.com will show up in the Referrals report which makes things even more confusing. You have to drill into your sources to find traffic from Gmail or Outlook webmail.

And if Google does not know what the Medium is, it will put that traffic into the Default Channel Grouping as (Other), which complicates reporting even more.

To see if this is impacting your data, go to the Channels report under Acquisition and looking for a Default Channel Grouping of (Other). If you see (Other) listed in your Default Channel Grouping, click on it to drill into your data.

In this account, after clicking on (Other), we see there are several Mediums of pdf and one named calendar pdf which reference PDF files on this client’s site which Google did not know what to do with. 

To avoid confusing results surrounding email referrals and links to your website that are included in email marketing messages, use campaign tagging to add parameters to every link in an email that directs visitors to your website. Although this is an extra step, taking the time to do this upfront will result in better data moving forward and will remove that (Other) category in your reporting.

Customize Your Social Channels

How much are you spending on your marketing channels, especially when it comes to social media? If you are a large business with a significant marketing budget for paid social placement, customize your social channels rather than use Google’s Default Channel Grouping. 

For those who do tag social media campaigns tend to use a Medium of Cost-per-click (CPC). This seems intuitive because it is paid traffic and permits you to easily view all your CPC traffic.

But traffic from a social channel is different than traffic coming from a paid direct response ad through a tool such as Google AdWords.

When CPC is used to tag paid social media campaigns, this social traffic is lumped in with traffic from all paid search channels.

To differentiate this traffic, you can create a New Channel Grouping for Paid Social campaigns or edit the Default Channel Grouping. Note that modifying the default channel grouping changes all data for new sessions so if you make a mistake, it’s permanent and seen by all account users.

If you do not want to edit the default, create the channel by selecting +New Channel Grouping in the Admin area of your Google Analytics account.

With your new Paid Social grouping, you add a source, such as Facebook or Twitter and a Medium, such as paidsocial, depending on how you have chosen to tag these campaigns. Once this Channel Grouping is saved, you will have data grouped in your Google Analytics reporting specifically for paid social traffic.

When you use Supermetrics for Google Drive to view your social traffic, you will have an additional medium of paidsocial to differentiate your paid and organic traffic as seen below.

Keep visitors on your website

A lot of sites inadvertently send traffic off their website after doing all the hard work of getting people there. In the ideal world, you keep people on your website so you can easily monitor all their behavior. 

However, this is tough to do because many companies use third party solutions, such as PayPal for payment or Eventbrite for event registration so they have people finish the checkout process on an external URL. If you are in this situation where visitors do not stay on your site when they finally take that action you desire, there are two settings to check to ensure visitors do not take all their data with them when they check out on a different site.

The first setting, the Referral Exclusion List, is the easy part, but note you must be using Universal Analytics in order to have this list available. If you do not use the Referral Exclusion list, a new session is triggered when the visitor comes back to your site after completing an action and the original traffic source that sent traffic that ultimately converted will not get credited

The above image shows that PayPal was added to the Referral Exclusion list in the Admin area of a Google Analytics account. As a result, Google Analytics will not start a new session when the site visitors come back from PayPal if they were just on your site. When the user checks out with PayPal, Google Analytics will look for PayPal.com on the Referral Exclusion list and since it is there, it will no longer create a new session.

That’s the easy part. If you need to know what they the visitor did while on a third-party site, you need to implement cross-domain tracking. The ability to do this depends on whether or not your third party payment or event registration tool allows you to add your Google Analytics tracking code to their pages. This is the only way to allow for the cookie to pass from your website to a website that you do not own. When Google does not see this cookie indicating cross-domain tracking, a new session starts. Since you want to pass cookie data back and forth between the two sites, before working with a third-party vendor, ask if you can add your code to their solution because it’s required for monitoring behavior on their site.

To Recap:

  1. Tag all of the links in your email campaigns. Even if you use an email newsletter solution that integrates with Google Analytics, you still want to add manual tags to every link that goes back to your website.
  2. Are you doing a lot of paid promotions on social media? If so, create a custom channel grouping just for this paid traffic.
  3. If you can integrate payment and event registration directly on your website, that is the ideal scenario. If you cannot, add your third party sites to the Referral Exclusion List. If you need to monitor behavior while the visitor is on that third party site, you will need to add cross-domain tracking.

About Tina Arnoldi

???????????????????????????????????? Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

DoubleClick Bid Manager and Adform Connectors Joining The Supermetrics Family

NEW CONNECTORS · 6-MINUTE READ · By Supermetrics on March 29 2017.

Supermetrics is happy to announce that not one but two new connectors have graduated from beta testing: DoubleClick Bid Manager and Adform. They’re all available to be selected from the data source list in our Google Sheets add-on’s sidebar.

DoubleClick Bid Manager Connector

Take advantage of the DBM reporting with Supermetrics! DoubleClick Bid Manager allows you to make programmatic buying, monitoring multiple image and video campaigns within a single environment.

With our DBM connector, you can easily pull all metrics with different dimensions and get a clear overview of your campaigns’ results. Using the Supermetrics add-on to automate your reporting, you can avoid the manual task of pulling out several reports from DoubleClick Bid Manager. The connector offers 60+ metrics and 90+ dimensions, pretty much everything you need for DoubleClick Bid Manager reporting, including ActiveView reporting metrics. It’s a great tool to add to your arsenal if you use DBM day in and day out.

Take a look at the custom report created with Double Click Bid Manager Connector

Apart from monitoring the usual campaign delivery metrics you can as well see how your video campaigns are performing with Video and ActiveView reporting metrics. Please note, that unfortunately Trueview:Views data is currently not supported by the DBM API at the moment, thus certain DBM metrics cannot be reported.

We wanted to keep the drawbacks of our new connectors totally transparent. And there is only one drawback: the DoubleClick Bid Manager Connector doesn’t load data as fast as other connectors in Supermetrics Add-on. That’s a limitation of the DBM API and unfortunately there is nothing our team can do about it.

Thus, you can select the metrics and dimensions you would like to see in your report, and enjoy your cup of coffee while our connector creates a DBM report for you. You can set up automatic refreshing while doing some other tasks, for example.

Adform Connector

Adform is an all-in-one digital advertising platform, similar to DoubleClick, and a leader in the Nordic market.

You can track delivery metrics (such as Impressions, Clicks, CTR) as well as cost metrics and engagement metrics. Site tracking statistics (e.g. views, visitors, exits, sales and many more), together with conversion and viewability metrics can also be added to the reports.

For example, you can report campaign performance metrics broken by channel, technology used or campaign type. Please note that Adform only allows running 500 API requests per day.


We launched these new connectors to get one step closer in helping marketers getting all their data into one place. Like our other connectors, not only do they allow you fetch data from individual data sources, but more importantly you can mingle data from different platforms to get a clear overview of all your marketing efforts.

Our goal is to let marketers fully enjoy the benefits of reporting automation. The team will work hard to add new data sources.

Want us to add some new data sources? Let us know in this short survey, and our team will do its best to make them available in Supermetrics Add-On.

Free trial

For those interested in giving a try to any of these connectors, we offer a free 30-day trial for our Google Sheets add-on. You can get started by installing it from the Chrome Store. Happy reporting!

Free Data Studio Template and Tutorial: Facebook Ads

GOOGLE DATA STUDIO TUTORIAL · 10-MINUTE READ · By Supermetrics on March 28 2017.

Google Data Studio is a lovely reporting tool for PPC and SEO. There are some great ways to use Data Studio to create beautiful reports. What’s even better, Google just made it globally available and free for everyone. We believe Data Studio will be a game changer for digital marketing reporting.

In this post, I’ll explain why Facebook is a problem for Data Studio and how to overcome it. If you want to dive straight in and copy my template, jump to this part of the article.

Here is the final look of the Facebook Ads template created with Supermetrics for Google Sheets and Google Data Studio:

The data source (or Facebook) dilemma

Understandably Data Studio now only works with Google data sources, such as AdWords, Google Analytics, DoubleClick, YouTube, etc. On the other hand, most businesses don’t confine their online marketing to the big G.

Many digital marketers we talked to want to use Data Studio for PPC reporting. And there is a behemoth in the PPC world, which is Facebook. Almost every company, that advertises online spends on both Google and Facebook, if not also on Bing, Twitter, LinkedIn and other platforms. Some small local businesses even lean more towards Facebook because of its unparallel targeting capabilities.

That’s when Data Studio’s lack of native integrations with other advertising networks becomes a show stopper for PPC reporting. Of course, you can’t have your AdWords reports built with Data Studio and your Facebook Ads, Bing, Twitter and LinkedIn reports built with some other tools. The difference in styles, formats and technical limitations on what you can include in your reports won’t make you look good.

Our solution: the Google Sheets connector

You shouldn’t stop using Data Studio just because you can’t get non-Google data. Did you notice that you can use Google Sheets as a data source? That’s where you can have a almost perfect solution. In a guest post we published on the official Google Analytics blog, we talked about how to get Facebook, Bing, Twitter & more into Google Data Studio. 

Don’t have the time or patience or interest to play around with Data Studio and Google Sheets? No worries. We understand the pain and decided to prepare ready-to-use templates to make it even easier.

All what you need to do is to copy the Google Sheet, copy the Data Studio template and connect this Data Studio report to that sheet.

You can most likely get it done under 3 minutes. Yes, only 3 minutes.

A free Facebook Ads template

Our 1st Data Studio template is for Facebook Ads. It uses the same styling and structure as the Sample AdWords Overview Report. provided by Google.

Follow the instructions below to duplicate it for your Facebook Ads accounts.

Make a copy of the Google Sheet with raw data.

Here is how the sheet looks like. Note it has multiple tabs.

Step 1: Copy the URL of the sheet:


Step 2: Add it as a Custom Template in the Template Gallery of our Google Sheets add-on.

Don’t know how? Find it out in this previous post.

Step 3: Give a name to the sheet. In this example, I named it as My Facebook Ads Data.

Set up automatic refreshing for the Sheet

Click ‘Schedule refresh & emailing’ in the Supermetrics sidebar or the Add-ons menu, to launch the trigger window.

Select the trigger type: refresh hourly/daily/weekly/monthly, however often you want to refresh this report.

Copy the Data Studio report

Step 1: Make a copy the Facebook Ads Overview Report

Step 2: Connect to the copied Sheet as a data source in Data Studio

When the report is copied, it keeps the original data sources as the default ones for the new data sources. Click on the arrow on the right to change it.

Step 3: Choose Create New Data Source

Step 4: Choose the copied spreadsheet and the worksheet Key Stats By Date, and click Connect.

Initially the calculated fields aren’t copied. You’ll have to create them yourself. It’s rather straightforward.

Use the small blue plus button to create a new field, type in the name and the formula, and then click on the blue Create Field button on the right.

Step 5: Then click Add To Report in the next screen.

Step 6: Repeat it for the other five data sources, without creating calculated fields, and finally hit on Create Report.

Here you go, your Facebook Ads report is ready!

How to create your own Data Studio reports via Google Sheets

There are only three steps really. 1. Pull the data into Google Sheets -> 2. Connect to that sheet as data source -> 3. Create your report

For step 1, the key is to pull the data into a separate sheet for each dimension you want to report. In this template, I have six sheets for the six dimensions I want to report on, date, campaign name, countries/regions, device, age/gender and campaign objective.

It’s pretty straightforward to to connect to a sheet as a data source

Just make sure you create a data source for each worksheet that you want to include in the report.

In the end, it’s all about creating beautiful reports in Data Studio. There is a bunch of tutorials and guides out there:

Two advanced tricks

Date format

Make sure the formats of your dates and times are compatible with the ones supported by Data Studio. Otherwise they won’t be recognized as date/time.

If you split data by dates, it would work perfectly OK.

You may run into issues if you split data by month or year. For example if When your data is split by year & month, it looks like 2017|01 in Sheets. And when this sheet is connected to Data Studio, these month numbers aren’t recognized as months.

The root cause is in Google Sheets there is no such a cell format as month or year. The values are always dates and just shown as month or year.

After hearing the same problem from many, we decided to develop a solution and added this Format results for Google Data Studio under Options. Make sure this box is ticked when you’re splitting data by week, month or year.

Watch out Aggregation

Data Studio uses Sum as the default choice for Aggregation.

Sum makes sense for some cases but not all. For instance, you would never sum up ROAS or conversion rates. Choose the Aggregation wisely for your metrics.

There are only six aggregation types Data Studio offers, Average, Count, Count Distinct, Max, Min and Sum. If none of them fits your needs, you’ll have to use calculated metrics or pre-calculate your metrics in Google Sheets before importing them into Data Studio.

It’s a beginning, not an end

Congrats now you’ve built you first FB Ads report in Data Studio. But you shouldn’t and probably won’t stop here if you also advertise on other networks like Bing, Twitter and Linkedin. You can follow the same way to fetch those via Google Sheets.

Or if you prefer using ready-made templates like this Facebook Ads one, signed up for Supermetrics for free and we’ll deliver more awesome templates to your inbox.

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Measuring the Performance of Your YouTube Campaign: Google Analytics and Adwords


If you already have business videos or the capability to create video content, YouTube can bring you a lot of traffic for very little money. But keep in mind this audience will be different than those coming from other marketing channels and you may discover short attention spans with the content you publish. So how do you know if your YouTube campaigns bring a positive ROI?

There are multiple ways to view the performance of your YouTube Campaign and I covered some of these basic metrics in an earlier post: Measuring the performance of your YouTube Campaign. In this continuation, I’ll provide additional ways to measure your campaign performance in Google AdWords and Google Analytics.

The goals of your campaign will determine which metrics to monitor in YouTube, AdWords, or Analytics and suggested metrics for each goal type are provided below.

Google AdWords Video Metrics

View performance

In your Google AdWords account, you will see raw numbers of views in addition to the view rate which advertisers are already familiar with. View rate is similar to the CTR for clicks and impressions on your other ad types. This will also show the average amount you pay when viewers watch your videos or engage with your ad. You can see the maximum costs for views, similar to the maximums you see for clicks with your search ads. These metrics indicate how many people are becoming aware of your brand.

Once viewers are aware of you, you want them to take the next step beyond viewing by clicking on your ad. Engagement includes clicking on cards on your video or your call-to-action overlay. Earned views also measure YouTube engagement because it indicates people watched other videos on your channel after seeing this initial video ad. Even better, some may choose to subscribe so you know they want to hear and see more from you. And of course likes are nice, but shares are even better.


Reach is how many people viewed your ad and how often your ad was shown to each person (as determined by cookies). You can also see how many times it was viewed for each viewer.

Video playtime (Watch Rate)

This measures how much of your video was viewed in quartiles: 25%, 50%, 75%, and 100%. If viewers rarely make it past that first quartile, it does not mean completing scrapping the video. You may be able to edit what you have into a shorter run time.

Segments – Network

On which network are your videos being displayed? Video Discovery ads (formerly known as In-Display ads) are shown next to related videos or in a YouTube search results page. In-stream ads are shown on YouTube as well as the Google Display Network. Since these are very different networks, you want to know if one format is better than the other both in terms of cost as well as views.

Segments – Mobile users

What about device type? Is there a difference in cost and views depending on whether the video was viewed on a computer, mobile device or a tablet? If most users view your video ads on a mobile device, you want sharp images that will stand out on a smaller screen.

Review the Video Targeting tab

If you are new to YouTube advertising or perhaps a little uncertain about your exact audience, you will want to target a broader group initially. As you gather campaign performance data, you may want to add or exclude demographics. Similarly, you may discover interesst, placements, or affinity groups to add or exclude. These metrics are all available in the Video targeting tab of your AdWords campaign.

That’s a lot of data available to you as an advertiser. We have data in YouTube. We have data in AdWords. Do we also need yet another place for data in Google Analytics? Yes. Because nothing we do in marketing happens in a vacuum. We use multiple channels and strategies to reach our prospects and we want to understand how our marketing channels may work in conjunction with each other.

Google Analytics Video Metrics

YouTube Visitors

This is a simple metric in Google Analytics and a good starting place available under Acquisition. Who learned of your web site from YouTube (New visitors) compared to your other channels? You can drill into Video Campaigns specifically or compare it in the context of all your existing AdWords Campaigns.

YouTube Referrals

Remember that YouTube is a social channel. So while you will want to review this in the context of your AdWords campaign in Google Analytics, also compare it to the other social channels you use to drive traffic – both paid and unpaid – as well as other referral sources. From here, you can view basic engagement metrics as well as also conversions. For example, do your YouTube visitors complete the goal of signing up for your email newsletter?

Multi-Channel Funnels

You may not see direct conversions with your YouTube visitors, such as immediate email newsletter sign-ups. Visitors may come to your site but not complete a desired action during the first visit. With Multi-Channel Funnels, you can see the visitor’s journey through your website and the influence of video. By understanding the impact of each marketing channel compared to the others, you can make better decisions about how to budget moving forward. 


Determining the purpose of your paid YouTube campaign will guide your decisions about what to measure. And these metrics are available in multiple places: YouTube Analytics, AdWords, and Google Analytics. Start with YouTube Analytics to see how your videos perform on their own, not compared against your other channels. Next spend some time in AdWords to view how paid campaigns are contributing to your goals and bringing a positive ROI.

Finally, explore YouTube performance in Google Analytics to determine how your marketing channels work together, keeping in mind that a YouTube campaign will likely bring different results than your other marketing channels and explore that data with the goal of brand awareness. Of course, brand awareness does not immediately translate into revenue, but website visitors do need to first hear about you before doing business with you so brand awareness is a worthy pursuit.

About Tina Arnoldi

Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

Every Click Counts: Compare Success Across Facebook Ads, Twitter Ads and Other Platforms

ADVERTISING ON SOCIAL PLATFORMS · 10-MINUTE READ · By Misty Faucheux on March 13 2017.

To ensure that we are reaching our audiences any place where they might be consuming media, marketers run paid campaigns on many different platforms. While individually we can tell the success of the campaigns, oftentimes we need to provide comprehensive numbers to our stakeholders – for example, overall impressions, clicks and engagement. Yet, most social networks use terms like “reach”, “follows”, “likes”, “retweets”, etc. So, how do you compare apples to apples on the different platforms?

Grouping by Type

Social networks have always had diverse terminology for what actions on their platforms. Part of this must do with branding – to distinguish the one platform from its competitor. While calling a post a “Tweet” or a share a “Retweet” helped Twitter coin terms that became recognizable with its brand, it also created confusion for marketers trying to showcase their successes.

Luckily, on the advertising side, many of the expressions that we’re used to on platforms like AdWords and Bing (think impressions and clicks) are consistent with the terminologies being used on platforms like LinkedIn and Twitter. Facebook, however, uses the term “Reach” or “People” to reference impressions. Yet, the meanings are quite similar.

Google AdWords defines an impression as “how often your ad is shown. An impression is counted each time your ad is shown on a search result page or other site on the Google Network.”

The Social Media Examiner defines Facebook Reach this way:

Facebook reach is the number of unique people who saw your content. It affects every other metric you can track: engagement, likes, comments, clicks and negative feedback. And that’s not all. There are different kinds of reach: post, page, organic, viral and paid.

Facebook breaks down the difference even further, saying that impressions are the number of times a post from your Page is shown. Reach, however, is the number of people who received these impressions. Reach is going to be slightly dissimilar than impressions since one person can see multiple impressions, meaning that Reach is going to be somewhat lower than impressions.

If we think about this in terms of AdWords, Reach is the equivalent of unique impressions. This allows us to then group unique impressions together.

While Facebook won’t provide exact overall paid impressions, you can use Reach as an impressions metric. You can combine these impressions numbers with impressions from, for example, LinkedIn or Twitter to determine as close as possible total overall impressions.

With Twitter, you always want to ensure that you are measuring the right types of “clicks”. For most of us, those are going to be “Link clicks” since this means that we’re driving traffic to a landing page or website. Twitter also has the following types of clicks:

  • Embedded media clicks: Clicks on a photo or video embedded in the Tweet.
  • Hashtag clicks: Clicks on a hashtag within the Tweet.
  • Permalink clicks: Only available on desktops, it’s clicks on a Tweet permalink.
  • User profile clicks: Clicks on the user’s Twitter handle, name or profile picture.

If you are measuring these types of clicks, then they may be better served as “engagements”, not clicks.

Engagement Measurements

Overall, engagement is going to be more like brand awareness metrics. Engagement can include anything from “Likes” to “Follows” to “Retweets” to “Mentions”. I’ve seen many social media analytics reports separate these out. Yet, unless you are specifically trying to increase the followers of a page or person, then these engagement metrics mean little to stakeholders who often only want to know if this will convert into measurable ROI.

In my experience, grouping these metrics together as overall “Engagement” or “Brand Awareness” is a better metric than the individual stats. Most of the social networks will provide an “Engagement Rate” percentage. You can total out the overall engagement rate across the different social networks and create a single column with this information. Then, you can add a percentage increase or decrease to show whether or not engagement is growing. For most clients and stakeholders, this is enough information and provides a better picture than individual engagement metrics.

LinkedIn breaks down actions similar to AdWords.

Facebook Reach is similar to unique impressions in other platforms.

Twitter groups different actions in the Results tab, including clicks, follows and engagements.

What Does Success Look Like on Each Platform?

Honestly, this is going to depend on your goals. As mentioned, we can fairly neatly break out “brand awareness/engagement” goals from impressions and clicks. If your client is a new company that is looking to grow their Facebook page Likes, then engagement and overall impressions are going to be the most important metrics.

Yet, for most clients, they want to know how their social media efforts are translating into ROI. This means that they’re interested in “Clicks” and “Conversions”. Facebook, LinkedIn and many other of the social platforms actually allow you to track Conversions within their platform as long as you have conversion tracking set up. These metrics can be combined with AdWords, Bing or similar conversions to provide a comprehensive picture of overall campaign success in a single view.

How to Showcase Success Across Platforms

You will always have stakeholders that want to see the individual breakdowns of each platform, which you should always have on hand. Many, however, want to see that their advertising dollars are being put to good use and that these efforts are leading to conversions at a reasonable cost per acquisition.

Creating a comprehensive, single view report with all the metrics from all your individual campaigns provides the big picture that might be missing from individual social media or advertising reports. While you can create your own report, third-party companies (like Supermetrics) have created reports that make it easy to import your data and quickly compare statistics.

You will more than likely have to tweak reports based on goals, especially if they’re subject to change. For example, you might want to focus initially on how you’re expanding overall brand reach. Yet, after month three, you will probably want to start showcasing conversions across funnels.


Every platform has its place in the biosphere of digital marketing. Yet, spreading statistics across so many different platforms can cause confusion among stakeholders, especially with the varied terminology. Consolidating data into a single view with simply-termed metrics can improve stakeholder understanding and better display overall ROI and success metrics.

Marketers should review each platform that they are using as well as the definitions of the individual metrics before combining metrics. You want to ensure that the stats are comparable before uniting them.

About Misty Faucheux

20140725_0031 Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

Use Case: Automating KPI Reporting with Leadfeeder

SUPERMETRICS USE CASE · 9-MINUTE READ · By Pekka Koskinen on March 7 2017.

Running a SaaS startup is like flying an airplane in the dark. By looking out of the window and using your senses you get some feedback on what’s happening, but the real trustworthy information comes from your instruments. We need to be always aware of how our business is doing and where we are heading. When steering the company to a new direction, developing new features for our product or testing different marketing campaigns, we need to have a reliable feedback loop to know if we are doing the things right. Without a proper analytics feedback loop we would not know what is working and what should be done next. KPIs are a vital part of our business development and they give the whole team and investors a real-time view on how we are progressing. That’s why a big part of my job as a CEO is to make sure we have the metrics in place and people have access to the information they need.

The old faithful Excel

I started out developing business analytics tools 10 years ago when I was running my first SaaS startup. Back then there weren’t any good business analytics tools available so the only way to do this was to make ad hoc queries to our database with SQL. With a bunch of joins I was typically able to answer any business question I had. This approach was fine for occasional one-time queries but not convenient for regular KPI reporting. I wanted to have my KPIs automatically updated in Excel spreadsheets. As a solution, we created a read-only replica of our production database which I then connected to from Excel using an ODBC driver. With this method, I was able to refresh the data with one click and use pivot tables to analyze and draw conclusions from it.

Nowadays, there are tools like Kissmetrics, Mixpanel, Google Analytics and many other business analytics tools which give you many important metrics off the shelf. I’ve used these but they cannot answer all business questions. A big part of the data I want to analyze isn’t sent to any third party analytics systems, but instead is stored in our own database. Since it’s not possible to send all data from our database to some other system, there’s still a need for direct queries to the database.

The main challenge with using Excel was that it was very difficult to share the reports. If I sent the spreadsheet to someone else, they couldn’t refresh the report with newest data without first installing an ODBC driver on their own computer. I would have also needed to give them credentials to the database.

Google Sheets to the rescue

When I started Leadfeeder a few years ago, I began looking for a better solution that catered to the modern cloud-based world. And since Google Sheets had replaced the use of Excel, I also focused on looking for a way to connect Google Sheets to our database with SQL. This is how I discovered Supermetrics.

I basically just searched for Supermetrics from Google Sheets Add-ons, added it and gave permission to access my Google resources. This added Supermetrics to my Google user so the add-on was then available in all my Google sheets. The entire process was very easy.

I then added a database connection, entered database credentials and edited a couple of firewall rules to enable access from Google server IPs to our MySQL business database. We run our services in AWS and created a separate read-only business database which is a daily copy of the production database. We could have used a straight replica which is easy to make in AWS, but we wanted to be able to select the tables and columns that are sent to the business database to prevent any sensitive information from being sent, like password hashes.

Creating the automatic revenue report

Our most important KPI report shows how the amount of users, accounts, purchases, churns and MRR (Monthly Recurring Revenue) are developing. For this, you need to store in the database daily changes for users, accounts and paid subscriptions. From this data we can retrospectively calculate how many users, accounts and paid subscriptions we had on any given day. Calculating these metrics for all days in the last two years gives us a nice view on how the amount of users, accounts, paid subscriptions and MRR has evolved. In order to get this done, you have to do some SQL magic with probably lots of joins and subqueries. MySQL workbench and someone who knows SQL are your best friends here.

From these metrics we can draw nice graphs and calculate growth and churn rates for each month and week. In the Supermetrics settings, I added a trigger to automatically refresh the data every night. For the most important reports I’ve also configured a weekly email delivery for the team. The spreadsheet is accessible online for the whole team as well as investors, making our work transparent to everyone. When talking with new potential investors, they have been very impressed with how we have our business metrics updated and available at all times.

In the revenue KPI report we have two tabs for raw data from our database and four tabs for different pivot table analyses. More specifically, the tabs we have are:

  • Daily KPIs. Daily amount of new users, trials, subscriptions, churns and MRR.
  • Monthly KPIs. Same information as in daily KPI tab, but grouped on a monthly level using pivot.
  • Subscription changes. A log of changes to our subscription base, including daily information about who subscribed, downgraded/upgraded, and churned and what the monetary effect was on MRR. New subscribers are divided into three categories, new sales (customer bought their first subscription), expansion sales (existing customer bought for another website) and reactivations (churned customer came back).
  • Monthly subscription changes. All subscription changes aggregated on a monthly level using a pivot analysis.
  • MRR change by country. This is a pivot table where we have the MRR change for each country for each month. From this report we can see how we are progressing in each market region.
  • Gross and net churn. A pivot table about how much MRR we lose each month. The difference with gross and net churn is that for gross churn we only look at cancellations and for net churn we take into account reactivations, upgrades, downgrades and other expansion sales.

In addition to the revenue KPI report, we’ve created tens of other reports with Supermetrics for analyzing how the usage of different features correlate with conversion from trial to paid and how traffic from different marketing channels convert into trials.

Just give it a go

Working with Supermetrics is easy, but in order to implement smart reports you need to have some SQL skills and know how to use pivot in Google Sheets. There might be a learning curve in the beginning, but once you learn this it’s super quick to create powerful new reports. Typically it takes me about 30 minutes to create a new report and have it automatically updated. We’ve learned a lot from our business and we’ve been able to develop our sales, marketing and product development based on facts. Investors have been very pleased about having such a transparent and real-time reporting in place and new potential investors have been impressed on the level of business analytics we are having. I would recommend having this kind of reporting in place for every SaaS startup founder.

Pekka Koskinen

Founder and CEO of Leadfeeder

About Leadfeeder

Leadfeeder is an online service which tells who have been on your website and what they have done there. It uses data from your existing Google Analytics, so you don’t need make any changes to your website. It also connects to your CRM to get updates on CRM on website visits from interesting companies and to Mailchimp to identify email addresses of website visitors. Learn more about the company by clicking this link.

10 Reasons Why Google Analytics is Not Increasing Your Bottom Line

GOOGLE ANALYTICS TIPS · 7-MINUTE READ · By Paul Koks on February 27, 2017 Google Analytics is a fantastic tool, but in my experience more than 80% of the companies actively using it, are not getting everything out of it. Or even worse, are not able to increase their bottom line. There are a lot of factors that determine how useful a tool is for your organization. In this post I will address several issues with Google Analytics that can prevent you from uplifting your ROI.

1. No or The Wrong Questions are Asked

To keep things easy I would say there are two phases:
  • Google Analytics implementation/configuration
  • Google Analytics analysis
Your implementation and configuration should be directly in line with your measurement plan. What is important for your company to achieve and what do you need to measure in order to accomplish this? You should put in enough efforts to answer these questions first. “You can’t optimize what you don’t measure.” Creating a measurement plan Finally you have set up your Google Analytics and gathered a month of data. Now it is time to dig through the data. Hey, but wait… Where are you going to look at? “Your analysis can only be as good as your question asked.” You can ask your boss or colleague to define a specific question, but if you have some experience you will be able to define some great questions by yourself as well! If you belong to an agency – working for a wide range of clients – this is an article about the art of asking questions†you don’t want to miss reading.

2. Incomplete Measurement Plan

In probably four of the five Google Analytics setups that I have audited in the last month, I found that there was a lack of useful event tracking in place. This is just a simple example of a big gap in the measurement plan. Not even fancy stuff like custom dimensions and metrics, but measuring simple interactions is neglected by many companies. Let’s assume you are an online marketer or CRO specialist. What can you accomplish if you only measure pageviews and not all important interactions on the website? These additional insights†deliver great value in understanding how your website functions and what your visitors are exactly using and asking for.

3. Inaccurate Configuration

In the first chapter I explained about asking the right questions. Sure, this is a great step, but if your configuration isn’t inaccurate or incomplete, these questions don’t make a lot of sense. Here is a 10-point list of things that often go wrong:
  1. Setup that lacks multiple views (raw data view, master view, test view etc.).
  2. Goals that are defunct.
  3. Important actions that are not set up as a goal.
  4. Default channel grouping that is inaccurate. -> (Other) traffic bucket is greater than 10%.
  5. Incomplete setup of referral exclusion list.
  6. Ecommerce site with goal and ecommerce values configured.
  7. Non-ecommerce site without goal values.
  8. Content grouping incorrectly applied.
  9. Incomplete list of filters and/or filters that adversely affect the data.
  10. Site search query parameter is not stripped from the URL.
Default channel groupings I could easily make a list of 100 items here. The point is that in many cases the configuration is inaccurate so you shouldn’t trust your data.

4. Domination of†Reporting Squirrels

Yes, sometimes you need to build reports, but if this is the main Analytics job in the company, you are doing things dead wrong. Make sure to minimize reporting time and maximize on doing meaningful analysis and optimization.reporting squirrel A great start to reduce reporting time is to†pay a visit to Supermetrics’ Google Sheets Template Gallery.

5. Misinterpretation of Analytics Data

This is a big one as well. There are many different reasons why you could possibly draw the wrong conclusion based on your data. Even if you have collected the best possible data in the world. Here are five†common ones:

6. Not Testing Your Findings

Google Analytics is not your final destination.

Your data collection process and data evaluation might or might not support a hypothesis for (A/B) testing. This is different from pure channel optimization. You still need to test, but not always by applying website changes. This could be as simple as changing your Google Ad title or bought keywords. Or investing more money in retargeting for example. But still you need to test here.

However, if you talk about website A/B testing, you need to test all your findings with multiple A/B tests to find additional proof that supports your hypothesis and data. All too often changes are implemented without testing your data findings first. And you know what, sometimes it will even negatively impact your bottom line.

7. Being Caught in Google Analytics Silo

Google Analytics is good at a lot of things, but not good at everything. Directly surveying your visitors – as an example – is very useful in addition to just collecting and acting on quantitative data.

It’s a great start if you correctly implement and configure Google Analytics, but make sure to take a broader approach in Analytics and Conversion Optimization.

8. Comparing Different Data Sources and Periods

Comparing different data types and sources can be valuable for sure, but make sure to know exactly at what data you are looking at.

Here are three†examples when things can go wrong:

1. Comparing Google AdWords clicks with Analytics sessions

Both metrics are useful, but they measure something totally different. A list of six reasons why this is the case:

  • Single AdWords click which results in multiple sessions.
  • More AdWords clicks in the same session.
  • Invalid AdWords clicks that still result in multiple sessions.
  • Cookie law implementation that results in less sessions than clicks.
  • Improperly tagged Ad URLs.
  • Website server doesn’t accept GCLID parameter.

2. Comparing on months instead of days

Let’s assume you compare March with February. March counts 31 days and February 28 (or 29).

This can make a huge difference if you compare on absolute metrics (10% more days in March compared to February). Make sure to choose equal data periods so that you don’t take the wrong decisions based on your data.

You could compare on a weekly or four-weekly basis for example.

3. Comparing without taking into account external events

Google Analytics annotations will help you to keep track of external events that might have a huge impact on your data.

If you make a month-to-month comparison, you need to know the context of your data in addition to the numbers.

This will enable you to make better data-driven decisions.

9. Not Telling Convincing Data Stories

Telling meaningful stories with data is what can make or break your Analytics efforts.

If you want to drive change, you have to go beyond simple numbers or Google Analytics screenshots.

Include stories, add names to each persona and even your HiPPo can be convinced to support your recommendations!

10. Not Visualizing Data

Visualizing data is something very closely related to my last point.

There are at least two reasons why you would want to visualize data:

  • This makes it easier to find relationships between certain data points; it might reveal website or channel mix areas for improvement.
  • It is one of the most powerful ways to†convey your message to any audience.

Make sure to read this article if you need some inspiration on data visualization tools!

This is it from my side! Any feedback is more than welcome!

About Paul Koks

Paul Koks Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.  

5 Tips To Improve Your E-Commerce

E-COMMERCE · 9-MINUTE READ · By Misty Faucheux on February 20 2017.

Marketing efforts are typically considered a success only if they drive leads and sales. While brand awareness is important, your stakeholders most often want to know that you’re converting your budget into profit. Yet, surprisingly many marketers don’t fully track everything related to their Ecommerce activity – or leverage that data to improve their campaigns.

Are you tracking the right data?

Most marketers understand the importance of setting up conversion tracking in AdWords and similar platforms. Yet, most only think about how many “conversions” they are receiving without ever considering that not all conversions should receive equal weight.

Take this for example: One recent client was tracking a variety of conversions: form fill-outs, gated asset downloads, demo requests, etc. The form fill-outs and the gated asset downloads were more “top-of-the-funnel” activities, i.e. downloading a whitepaper or viewing a video. In sales terminology, these leads would have to be nurtured before they would be considered a “hot” lead.

The demo requests, on the other hand, were actual hot leads since these were people potentially interested in using the product. Yet, both sets of leads were given the same consideration as far as total conversions, value and potential ROI. These leads, however, should have been weighted differently and dropped into two very different buckets: marketing qualified (MQL) and sales qualified leads (SQL).

Marketing qualified leads are all leads, i.e. every single type listed in the example. Sales qualified leads are leads that need to get to the sales people ASAP. These will be the leads that now need a salesperson to close the deal. The client is ready or near ready to buy.

Depending on the type of inquiry as well, higher value leads should be given priority, reflected in the value that it’s given in the conversion tracking fields. In order to make sure you calculate the lead generation value correctly, read this article.

Then in reports, higher-value conversions should be broken out from lower-value ones.

Gaining Value from Ecommerce Tracking

Oftentimes, we get stuck in the rut of simply looking at which campaigns are and are not converting, and for what CPA. You can, however, learn so much more if you dive deeper into the data.

With Google Analytics alone, you can track data like:

  • Revenue: Marketers should always compare revenue to spend, and not simply once per month. If in middle of the month you determine that lack of revenue is going to result in negative ROI, you should adjust spend and tweak the campaign.
  • Item Name: Understanding which products are being sold is important. If a product is consistently selling – with or without marketing’s assistance, then you might not need to put a lot of marketing dollars behind it. Yet, if there is a high-profile product that doesn’t really move, then you should shift more budget to this campaign and potentially add even a branding campaign to increase awareness.
  • Price: Price is especially important when it comes to total ROI. For example, let’s say that you’re spending $5,000 per month on a paid search campaign. You’ve made over 1,000 sales, but only on your lowest-cost product, i.e. $5.00 toy. While the overall sales look good, your ROI on this is flat. You’re not making any money on the product. Add in the cost of employees or vendors managing the campaign, and you’ve actually lost money.
  • Quantity: Quantity helps also you see which products or services are selling the best.

Leverage this data to determine individual campaign success. While total sales may look good, digging into individual campaign data often tells a story of one product carrying all the campaigns – as opposed to success all the way around.

Learning More About Your Customers

With a recent customer, we figured out that most of the conversions and traffic were coming from mobile, but the site wasn’t really mobile-optimized. This was hurting potential conversions. We decided that a landing page might be better in this scenario since it would be mobile-optimized. Understanding your customers is one of the first steps in improving your campaigns. You can get in-depth information on how and where your customers are consuming to better funnel marketing dollars.

With Google Analytics, you can obtain information on:

  • Demographics: Are more women than men consuming your products? What about a certain age group?
  • Geographic: For national campaigns, many marketers default to the entire country. But what if most of your conversions are coming from the West and East Coasts, and not the middle of the country? With these insights in hand, you could better target marketing dollars.
  • Interests: Google Analytics will show some interest data, including data on who’s converting. You can leverage this data to tweak messaging and targeting.
  • Mobile or Desktop: Like our previous example, it helps to know what type of device your audience is using.
  • Technology: Many of us may hate Internet Explorer. If the majority of your audience is, however, using it to find your company, your site better be compatible with the browser.

How’s Your Cart Doing?

We as marketers sometimes forget that no matter how much we tweak a campaign, that might mean nothing if our cart isn’t working for us. Luckily, we can set up funnels to see where users are abandoning the cart.

As long as you have goals set up, you can determine where users are exiting the purchase process. To do this, follow these steps:

  1. Go to Conversions, then Goals and Goal Flow.
  2. Select a goal from the dropdown menu.
  3. Move the mouse over each step in the funnel to determine the drop-off percentage.

You can then use this data to determine at which step most people abandon the cart. Do some investigation by going through the cart yourself. Compare this data to – for example – browser or mobile data to determine if these are barriers to completion.

You can find nice infographics by Statista, reflecting the most important elements for the customer in 2016 to give you an idea what you might want to check on your website:
Infographic: What's Important to the Online Shopper | Statista You will find more statistics at Statista

How to Keep Track

All this data can be found in your analytics platform, especially if you use Google Analytics. You must, however, have Ecommerce tracking set up if you’re trying to capture this data in AdWords. To enable Ecommerce tracking,

  1. Go to your Analytics account, and then the right Account, Property and View.
  2. Go to View, and select Ecommerce Settings.
  3. Ensure that the Enable Ecommerce toggle is On.
  4. Click Next step.
  5. Then Submit.

You’ll receive a lot of data from the Ecommerce report. A standard dashboard report, however, may still not be enough to capture all the data that you need for your stakeholders. A more in-depth report that showcases transactions, revenue, user insights, top channels, cross-channel interactions and more may better show successes, challenges and opportunities. While you can build these reports yourself from scratch, you can also leverage templates to assist you with the process. Then, tweak the templates based on your preferences and needs. Supermetrics offers a comprehensive E-commerce template (among many other templates that can be accessed from the Google Drive Add-On), that will show the breakdown of Traffic by different channels and reflect what audience works best in relation to the particular metric.

For best results, import different campaigns across multiple channels into a single report. This provides a comprehensive view of how the marketing efforts as a whole are performing. A single view cuts away the clutter of having to switch between different reports. Leverage the Multi-Channel Funnel reports in Google Analytics to show how marketing channels are working together to produce positive ROI. Even add the cart abandonment data to the spreadsheet, including the funnel reports.


Be prepared to tweak your report as time goes on. In my experience, the initial report oftentimes looks nothing like the report that you finally use several months later. As campaigns run, you’ll realize that some data is more important than others, meaning that you’ll add or subtract columns or sheets from your report. Plus, the client or stakeholders always have input on what they want to see.

Always review your reports. Even if you only have monthly reports, review this data on at least a biweekly, if not weekly, basis. These insights will help you gain insights into what’s working and what may need to be eliminated.

About Misty Faucheux

20140725_0031 Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

Use Case: How to Avoid Google Analytics’ Sampling

SAMPLING · 9-MINUTE READ · By Ruben Ugarte on February 13 2017. If you’re heavy user of Google Analytics, then you know about the dreaded “sampling issue”. If you don’t, then let’s see how Google themselves describe sampling:
“Sampling in Analytics is the practice of selecting a subset of data from your traffic and reporting on the trends available in that sample set. Sampling is widely used in statistical analysis because analyzing a subset of data gives similar results to analyzing all of the data. In addition, sampling speeds up processing for reports when the volume of data is so large as to slow down report queries.”
We recently worked with a client who was constantly running into sampling issues (more than 500,000 sessions per month) which meant that we needed to find a way to work with the unsampled data without spending hundreds of hours banging our heads against the wall. Let’s take a look at how we solved the Google Analytics sampling issue without going crazy.

Why Sampling is an Issue and How it Can Hide Crucial Issues With Your Data

The first obvious issue of sampling is that you aren’t seeing 100% of the data. This means that the numbers you’re seeing aren’t exact. You could have 26,000 visitors from Organic Search or you could have 49,000 visitors.

30% sample might be too small even for trends.

This kind of ambiguity is the opposite of how we expect analytics to work. The whole reason why we even decided to use Google Analytics was to get accurate numbers on our traffic and users. The second issue depends on how big the sample is. Sampling is meant to show you the trends within your data. This means that if Organic Search is responsible for 50% of your traffic in your sample, it should be around the same number if you were to look at the complete data set. However, this changes depends on how big your sample size is. If the sample is 90% of all sessions, then the overall trends are likely to be accurate. However, if the sample is less than 1% of all sessions, then even the trends themselves could be completely wrong. Sayf Sharif from Lunar Metrics talks about how even a 50% sample can hide issues in the data:
“Even at higher sample rates we’ve noticed issues. Once we detected an upwards of a 10% overall change at a near 50% sample. A client site when compared month to month, year over year, showed a 5% increase, with a 48% sample. However, when we looked at the data unsampled, we were able to show that instead of improving by 5% it had actually decreased by 5%. That’s an issue.” – Source
One of the biggest issue that we have seen when working with clients is getting them to trust the data. If you can’t trust your data, you won’t take it seriously and you might as well not have it. Sampling can create a distrust of the data and make it irrelevant inside your company. There’s a few different ways of avoiding the sampling issue but let’s focus on two: within the GA interface and using the Google Analytics API.

Simple Workarounds to Sampling Within the Google Analytics Interface

The GA interface is the easiest way to work with your data so avoiding sampling here is important. You have 3 options if you want to avoid sampling:

Option 1: Change the date range

Sampling starts when you have too much data which means that you can reduce your time period to avoid sampling e.g. 2 weeks instead of 1 month. The issue with this option is obvious. You may need to look at a whole month and not just 2 weeks. You could try combining two date periods (2 weeks at a time) to get a month but that isn’t perfect either.

Option 2: Increase the precision of reports

Google Analytics lets you increase the precision of reports. This button is available near the date range as seen in the image below: Moving the setting to the highest value of “Higher Precision” doubles the sample size that you can work through. If your sample size is high to start with e.g. 70%+, you could most likely avoid sampling altogether by increasing precision.

Option 3: Stick to Standard Reports

The Standard Reports in Google Analytics are never sampled. These are the core overview reports that you find under nearly every section. For example, we can see the “Audience Overview” report below showing all the possible data even though the numbers are high enough to justify sampling. Our client couldn’t use any of these workarounds. We needed to view long date periods such as an entire year and we needed accurate numbers for key metrics like pageviews, sessions and bounce rate. This meant that we needed a fast way of pulling unsampled data from Google Analytics. We decided to work with the Google Analytics API.

How We Avoided Sampling by Using the Google Analytics API + Supermetrics

The Google Analytics API lets you export all your data into a CSV or Excel file. It really is quite magical once you get the hang of it.

The Query Explorer lets you limit results to avoid sampling.

The API also lets you limit how much data you export at any given time which means you could limit the sampling within the data. Instead of pulling data for 1 month, you can pull data for 2 weeks and then do 2 exports to get the complete month. This works well but it can become a bit of pain if you have to do it multiple exports or if you need to split your data across 20 different queries and then combine that data into one file. We decided to use Supermetrics for Google Drive to help us streamline this process. After we installed the addon to Google Sheets, we got access to the sidebar below:

The Supermetrics addon in Google Sheets.

This interface matches what the Query Explorer API tool is looking for but it makes your life easier in a few important ways: 1. You can ask Supermetrics to “avoid sampling”. This doesn’t always work but it worked in most of the queries that we did. Supermetrics will break your query into multiple queries behind the scenes to avoid sampling. 2. Dumps the data straight into the Google Sheet. The addon adds the data to the Google Sheets which is where we could work with it. This meant that even if  we did 3 queries to get all the unsampled data, it would all be dumped into the same spreadsheet. 3. Once we created a query, we could edit it or use it create slightly similar queries. We were doing regional analysis which meant that we were looking at the same numbers except we would filter out by different regions e.g. California, New York, etc. We could create our query once, and then simply edit the filter to the change the State without having to create the query from scratch. 4. We could create advanced segments inside Google Analytics and then use them with Supermetrics to get specific metrics and dimensions. This simple interface saved us 35+ hours in our reporting work. We didn’t have to manually piece together multiple files and all of our unsampled data was in one Google Sheet. You can view a short 5 minute video here on how you can start using Supermetrics to analyze millions of Google Analytics hits and the best tips that we learned from this project. If we made a mistake with a query (which happened often), we could simply run the query again and get new data. We could magically go through millions of sessions without breaking a sweat.


Sampling in Google Analytics will continue to be an issue especially since Google doesn’t offer an affordable option beyond Google 360 (which starts at $150,000 a year). In the meantime, you could try a few of these options to get around sampling and start working with all your data. Do you have any other useful workarounds to this issue? Let me know in the comments.

About Ruben Ugarte:

Ruben Ugarte is the founder of Practico Analytics which helps companies get better insights out of Google Analytics and similar tools. I put together a short video that will show you how to start using Supermetrics to analyze millions of Google Analytics hits and avoid the sampling issue. You can download this free 5 minute video here.

Measuring the performance of your YouTube Campaign: Tips

YOUTUBE CAMPAIGN · 8-MINUTE READ · By Tina Arnoldi on February 7 2017.  

With traditional print ads, you don’t know how many people are actually viewing them. Even with pay-per-click advertising, you can view impressions but that still does not mean the ad registered with someone. According to Google, TrueView ads are “built on the promise that you’ll only pay when someone chooses to watch your video ad.” Viewers are shown ads that may be of interest based on their demographics, interests, or placements where the ad was viewed and viewers make the choice to engage with your video.

Introduction to TrueView

There are two different types of TrueView ads and understanding the difference is important.  With in-stream ads, they play either before or during another video on YouTube. Viewers see 5 seconds of an ad before they have the option to skip it. If they watch the full video or 30 seconds of it – whichever is longer – advertisers pay for that view. With video discovery videos, these are shown alongside other videos, in the search pages on YouTube, or other Google Display Network websites.  Advertisers pay when the person clicks on the video, choosing to engage with it.

Determining Success

How you determine success is based on the type of TrueView ad you run as well as your goal of the campaign. A meaningful goal for most brands – especially new ones – is to increase awareness and increase the likelihood of a sale. Although the experience of consumers is not linear; when determining success, think of consumers in categories of knowing or not knowing your product/service, in the stage of weighing different options once they become familiar with brands, or taking action and buying from you versus your competitor. For viewers who are not yet aware of your brand, you may monitor views, impressions, and unique users. In the consideration stage, you will would check watch time and view-through rates. And finally the action stage is the clicks, calls, signups or sales – when people take that action to buy from you.

YouTube Analytics dashboard

The main sections on the YouTube Analytics dashboard are real time metrics, watch time reports, and engagement reports.  Real Time data  is an estimated number but can give you initial insights on your recently published videos so you are not waiting several days for the initial results.  Watch time has key metrics for all campaigns because it tells you how long people view your videos on average. If you have a three minute clip that you think is very reflective of your brand and has solid messaging in it, but people only view one minute, all that work in the last two minutes of the video is irrelevant. Videos with a longer watch time are deemed by Google to be more relevant and are shown higher in search results because they indicate user retention.

However, if your watch time is low, it does not mean automatically abandoning the ad. Change the title or description of your video to be more reflective of the content. Optimize it so you attract the right audience for your clip. Use annotations in the video to make your video more interactive.  This invites people to stick with you until the end and are part of the engagement metrics described below. Experiment with the different features available with YouTube before abandoning your ad.

Engagement metrics are vital to all advertisers and are measured when people like, comment and/or share a video.  The desired action depends on the purpose of the video. If you have a short training for your product and invite user feedback, then comments are a valuable metrics. And make sure you respond to all of them – even the negative ones.  If your video is humorous, you probably want likes and shares, including shares on other channels, such as Facebook where your viewers help spread your message across the internet. The subscribers report is also valuable to see when you lost or gained people. What video were they watching when they subscribed or unsubscribed?  Dislikes are important if you receive a lot of them. In that scenario, you may want to invite comments to understand why your message did not resonant with a specific audience.

Case Studies

YouTube videos can be utilized well for most brands and work especially well for companies selling an experience – most of the time. Below is one where the video was not performing well, but the advertiser saw the negative numbers quickly and paused it for changes. This is a consulting business that was describing services in a three-minute clip. It could be the clip was too long or the clip was just boring. You’ll see that only 1% played the video to the end.

It gets even worse. The average view duration for this video was less with YouTube advertising (15 seconds) than with organic traffic from external websites (1 minute 2 seconds). So there seemed to be an issue with the content and the messaging. That’s why it’s important to catch these things early.

The next few screens are for a business selling outdoor adventures. They are selling an active experience so showing people what to expect was a good strategy.

This was targeted to women under 50 years old and set up as an in-stream ad. The initial thumbnail seemed to be engaging since the view rate was 27%. And 10 clicks to the website was also a good start. Remember there are multiple metrics to consider in measuring performance. Viewing the video is good but a call-to-action that’s interesting enough for a website visit is even better.

The next screen is for the same company with additional metrics. The number of earned views is five, meaning that as a result of watching this initial clip, there were five views on other videos for this channel. We’d like to see that number be higher so perhaps a larger variety of videos on this channel would help. 

Also note the video was not played to the end by most people, with only 27% of viewers making it through the whole thing. As more data is gathered, we can watch the video with a critical eye to see what the message is at the 25%, 50%, and 75% mark. It could be that the video’s core message was presented very early on without giving a reason for people to watch the full clip. So the length of future videos can be shorter.  The thumbnail and description may have drawn people in but not kept them engaged.


It is difficult to set an industry benchmark for ad performance for videos. It varies so much and you do not know the KPIs of your competitor. Instead, set your own benchmarks for what success looks like for you. Compare your YouTube campaigns to past campaigns on other channels. 

Like with all digital marketing metrics, remember that metrics are only numbers. You are the one who knows your brand’s goals and KPIs that result in successful campaigns. With almost one-third of all people on the internet using YouTube, it is no longer optional for brands to use video in their marketing.

About Tina Arnoldi

???????????????????????????????????? Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

Use Case: How Reprise takes advantage of Supermetrics

USE CASE · 6-MINUTE READ ·  By Pablo Contreras on January 30 2017.

In this blogpost Pablo from Graphene (the company which is currently a part of Reprise Media) will tell about how Supermetrics is used in their team and provide you with hints on what tasks could be accomplished with JSON/CSV connector.

What is Reprise?

Reprise is a global digital marketing agency, focused on performance, therefore our main work is on Google AdWords, Facebook Ads, DoubleClick and Google Analytics. Our clients are mostly e-commerce websites who are interested in improving their ROAS constantly, but also we have clients focused in branding but struggling with fixed budgets.

To optimize our efforts, we can rely on Supermetrics to get data for our reports for every client and follow up on budget consumption, letting us only spend time to analyze and take action. Besides that we use Supermetrics in special ways to do more than reporting.

Special campaigns dashboard

Some of our special campaigns run for a short time and are very demanding in terms of optimization and reporting, like a Cyber Monday. Using Supermetrics we can create custom reports in Google Sheets with scheduled queries updated every hour like this one.

In these reports we show different KPIs around the purchase funnel, like spending though marketing platforms (cost, impressions, clicks and CTR), website traffic KPIs (sessions and bounce rate) and online purchase revenue KPIs (revenue and transactions split by product type, which is a custom dimension in our Google Analytics). This report is built through multiple queries and then using formulas and charts we show the data in a dashboard format that we can share with our client through a URL that can be accessed anywhere, since Google Sheets can be accessed through a mobile device too. Using this we can avoid constantly reporting or being asked multiple times a day how is the campaign performing and giving us time to discuss decisions on how to improve the performance.

Avoid accidental overspending on Facebook

We also rely on Supermetrics to save money. With query scheduling and emailing we can create alerts if a campaign on Facebook Ads have set daily budget, we don’t use this because usually leads to overspending.

We have scheduled a daily query to look at the daily budget for every campaign on Facebook Ads, if the sum of daily budgets column is higher than 0 then Supermetrics sends an email alert with the report using the conditional emailing feature. This can be really useful!

Create product feeds with Supermetrics

Supermetrics has recently released a JSON/CSV connector which is awesome. We started using this connector to create feeds for dynamic creative optimization among all marketing platforms showing updated data pulled in JSON format. The main challenge was that JSON data is not easy to place in a spreadsheet automatically, and in Google Sheets the only solution is to create a script, which involves coding and maintaining. Supermetrics solved this!

Our main client has an API to pull product and price data from their e-commerce in JSON format, with this connector we have a reliable way to place that data on Google Sheets. With that data we create different product feeds with updated data for dynamic ads on Facebook, Google, Criteo and DoubleClick Studio, updated every hour through the query scheduler. Finally, we connect those feeds with each marketing platform and the result is ads that have the most updated price pulled directly from the e-commerce using this connector.

Though there are a lot of dashboard tools in the market, I think Supermetrics for Google Sheets is the best way to create anything you want with your data without the hassle of coding.

About Pablo Contreras

Pablo has been working in digital marketing for 6 years and his main focus is on analytics and real-time media buying. He currently leads Graphene’s Performance Hub, the biggest team in Reprise Media all over Latin America, which works exclusively for LATAM Airlines providing real-time media planning, buying, optimization and reporting for LATAM in 13 markets, from Santiago, Chile. You can connect with Pablo on Linkedin


Property Sets: Determine Your Overall Property Success

PROPERTY SETS · 6-MINUTE READ ·  By Misty Faucheux on January 23 2017.

It’s been nearly a year since Google introduced property sets. When Google released property sets back in spring 2016, marketers rejoiced since they could now see total clicks and impressions of their different properties. Property sets let you consolidate different sites, apps or mobile sites into a group or property set within the Google Search Console. Then, this information can be downloaded into a single report.

Initially, property sets were limited to only the Search Analytics information for the different properties. This meant that you couldn’t get full data on the other views. Google took note of users’ concerns and expanded their property sets in December 2016. Now, marketers can get information on usability, accelerated mobile pages, rich cards and more.

Leveraging Property Sets

Setting up a property set is quick and easy. To create your first property set, follow the below steps.

  • Log into the Google Search console.
  • You’ll see Create a Set on the right-hand side. Click the button.
  • Give your set a name. This should be the client, company or something similar, especially if you’ll be creating multiple property sets.
  • Add the properties that you wish to monitor. (Only verified properties can be added to sets).
  • Click Save changes.

It can take 24-48 hours to start gathering data. Once it does, however, you’ll be able to compare any available data within the reports. While this won’t be an issue for most people, enterprise-level companies should know that they can only group up to 200 properties.

Note: If your property isn’t verified, it must be verified first. You must also be at least a verified restricted user on All Set Members to add a site to a property set. If not, you should ask your client or the company to change your permission access level.

Also, if you lose ownership to a property, then the entire set will become null and void. You must either request access again to the property, or create a new set without that property. Further, you cannot share property sets with other users (unlike Dashboards, etc.). Property sets can only have one owner. So, if a stakeholder is wishing access to it, you must either send them a report, or give them access to your Search Console.

Reporting Advantages

There are some major advantages to property sets. For a recent client, we were trying to compare two different sites: a legacy site that the company was migrating certain products away from, and a new site. The company had been taken over by a much larger corporation, so the new site was going to be incorporated into the existing larger company’s domain.

Some of the products, however, were going to remain on the legacy site. The client knew that some traffic loss would occur as is normal with any migration. The goal was to determine how much of a hit would occur and where it occurred (i.e. which pages or keywords). Knowing that the site would now be split between two different sites, we had to monitor both sites to determine what was happening both pre- and post-migration.

We starting monitoring both sites to determine if search volume was taking a hit. We leveraged property sets to monitor the Search Analytics of each site, especially in terms of overall traffic, search queries and pages. We wanted to make sure that traffic as a whole didn’t deteriorate, and if it did, move as quickly as possible to correct it from an SEO-standpoint.

While this is only one example of how to monitor changes across properties, there are many other ways that you can also leverage these reports. For example, many companies have subdomains for different products or even blogs, or they have separate mobile sites or even different apps. In the past, it was impossible to automatically view total traffic. Instead, it was more of a manual process.

Subdomains, Apps and Mobile Sites

The main advantage of property sets is certainly its ability to consolidate numbers for larger companies. Subdomains and mobile sites all have URLs like your main website. Simply add the URL of these to your property. To add a mobile app, you’ll need add the app address, or you’ll need the owner of the app to add you as an app owner or user.

If you’ve ever had to perform analytics reporting for enterprise-level companies, pulling together the total analytics results for all the properties can be painful and extremely time-consuming.

Most reports require not only the individual breakdowns (which are relatively easy to obtain from Google Analytics or similar properties) and the total numbers. Issues arise when you try to pull together the latter.

If you need to connect the Search Console to your Google Analytics property, follow these steps:

  • Log into your Analytics account, and go to Admin.
  • Go to Property, and then Property Settings.
  • Go to Search Console Settings, and add your website to the Search Console.
  • Select the reporting view that you want to see.
  • Hit Save.

For example, we were working on the analytics for a large IT company. Each month, we had to pull together a spreadsheet that included the individual property numbers and a full tally. It was inevitable that at some point during a span of a few months or so that the formulas within the Excel document would get messed up because of changes by different parties – or simply overwriting. So, every month, we would up have to manually add up the different properties to ensure that the comprehensive number formulas were working.

Needless to say, this one report could take hours to complete. Yet, the spreadsheet was the only way to ensure that we could see how all properties were performing since the subdomains were being tracked via different analytics codes. Now, the property sets would eliminate this problem and show all clicks and impressions – truly a major advantage over the more manual process.

Note of Warning

While property sets make it easier to obtain the complete health of various websites, mobile sites and apps, you should always look at individual properties to determine if any singular issues are arising. The comprehensive views will lay out if there are any new messages or critical issues, and overall Search Analytics data and more.

Usually, however, you want to dig into individual properties, especially if you are tracking certain keywords or pages. The comprehensive property set view will give you the big picture. You still, however, need to dig into individual properties for the minutia that helps us determine overall site and search wellbeing.


Property sets help marketers show total big picture stats. This is especially helpful if you are managing multiple properties and are trying to demonstrate to stakeholders the effectiveness of global campaigns. It also eliminates the painful process of spreadsheets or manually tallying of overall stats.

You should, however, still have your individual breakdowns to show how each property is doing. Aggregate stats sometimes don’t lay out everything going on with your account, and you might be missing out on important issues, successes or failures if you choose to only review property sets.

About Misty Faucheux


Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.


New Year, New Connector: Custom JSON/CSV

NEW CONNECTOR · 4-MINUTE READ ·  By Supermetrics on January 18 2017.

Many of you have requested us to add data sources, that we don’t yet support. And there there’s a big variety in them: from SEO and A/B testing tools to companies’ own CRM systems as well as public data. While our engineers are working hard on the new integrations, we have to admit we can’t make everything happen overnight.

BUT we really want you to be able to fetch data from whichever data sources you need. That’s why we decided to develop a JSON/CSV connector as the first thing in 2017.

This connector allows you to fetch data from any data source in JSON, CSV or text format and transfer it to Google Sheets.

Benefits of the connector

There are three main ways you can use Custom JSON/CSV connector to your advantage:

1. Cross-referencing with public data like weather and public holidays

You can easily get useful data such as weather, public holidays, population and demographics from public sources via their APIs (for example, one list of publicly available sources can be found here). The data can be used in cross-referencing with your campaign and analytics data in numerous ways.

A few ideas on how you can use this data:

  • Import weather data to see how the weather affects your traffic and campaign results
  • Fetch city population data to see if there are different usage patterns in big cities vs small towns
  • Get national holidays’ dates to help analyze dips and spikes in traffic

2. An “ad-hoc” solution to fetch data from SEO tools, CRM systems and other sources

Another sizeable benefit of JSON/CSV Connector is that it can act as a quick solution to pull data from multiple data sources, connection to which has not been developed by Supermetrics yet.For instance, you’re running lead generation campaign and want to get the leads from your CRM system to the same Google Sheet where you have your campaign data.

Then, you can ask your developers to export that data from the CRM into a JSON or CSV format and then use our new connector to get that data into your Google Sheets. The files are stored on your server and can be updated on daily basis, with data in Google Sheets being automatically refreshed (if you set this option). That solves the problem of security – there is no need to store data on the external servers, and you can easily share your Google Sheet reports with your clients and colleagues.

3. Connect to Databases that are not supported by Supermetrics yet

In addition, you can use our new connector in case the Supermetrics Database connector does not support your database type (currently there are 4 types that we support: MySQL, SQL Server, Oracle and Google Cloud SQL). You can export that data in JSON or CSV format and pull it into your Google Sheets via this new connector.

How to use the connector

To access the connector, launch Supermetrics for Google Sheets Add-on and choose “Custom JSON/CSV” from the list of the data sources.

Then, in the query type you should write the URL you want to get data from. Do not forget to choose the type of your data (JSON, CSV or TXT). Additionally you can specify the request and the HTTP headers.

For your convenience, you can also put the URL into any cell of the sheet and reference that cell in the “Type URL” field on the sidebar (e.g. “Type URL =J1”).

After you set all the parameters, simply click “Get Data” button.

Bonus feature: JSON Path

If you only want to get certain values from the JSON response, use our JSONpath extractor on the sidebar. Below is an example of how you can take advantage this option

Let’s say you want to get a particular weather condition (e.g. “Light snow”) for a specific city. First you have to specify the city you want to get data from by constructing the API call. For example, the city we want to get data from is London. The API call for London from wunderground.com (containing your API key in the middle) will look like this:


Without specifying any weather conditions in the JSON Path, the weather data for a particular city in your Google Sheets will look like this, with many more rows of data continuing to the right:

We should construct the path to get the weather condition in the following way (according to the wunderground.com guidelines):


After we have specified the JSON Path the result of our request will look like this:

You should find guidelines for constructing paths and data features/parameters on every website you want to get publicly available data from.

You can check whether your path is correct by using JSONPath Online Evaluator, available here. The general guidelines for creating JSON paths are available via this link or by clicking the “?” sign next to the “JSON Path” on the sidebar.

Useful Tip: Copy the result as a formula

In addition we have another great feature to offer – now you can create a particular query as a formula with and copy it to the other cells. Let’s take a look at the above mentioned example with the weather data: say, you want to get the particular weather condition (e.g. “Mostly Sunny”) for each city without having to specify the URL in the sidebar multiple times.

First, we input the URL and the JSON Path on the sidebar to specify the data that we want to get for a particular city. Next, you should choose “Get Data Using Function” from the “Get Data” dropdown menu.

After the query is completed you can copy the result as a Google Sheet formula.

This is how the table looks like after you have copied the first formula. The URL’s were replaced in accordance with the cities for which the weather data had to be received.


We built this custom CSV/JSON connector to enable you get meaningful data from the sources Supermetrics doesn’t yet directly integrate with.

This is just one new feature we’re releasing recently. Q1 has much more to come – stay tuned to see what else we have to offer!

We are interested to hear from you – try our CSV/JSON connector and leave a comment below to tell us how you use it:)

Use Case: Why Supermetrics Is valuable for Digital Uncut and their Clients

SUPERMETRICS USER CASE · 5-MINUTE READ · By Sam Martin-Ross on January 16 2017.

Over at Digital Uncut we use Supermetrics to streamline our internal processes, this frees up time to focus on more important and interesting aspects of our clients’ accounts.This means we can provide a level of service, account management and analysis beyond many larger (and more expensive) agencies.

As a small and growing PPC & SEO agency, staying on top of accounts and continually improving ROI can easily eat up a lot of our already limited time.Without efficient account management processes, simply staying on top of our accounts would mean significantly less time for strategizing, client contact and long term planning.That would impact both the results we can deliver for clients, and the growth of our agency.

Supermetrics allows us to pull data from multiple sources such as; Adwords, SEM Rush, Bing & Facebook into a single view. This provides benefits across all aspects of our business such as; client account performance, reporting, in depth analysis, and opportunity finding.

Spend Management

When it comes to spend management, prior to using Supermetrics this was done manually. We now use Supermetrics to pull data daily from all channels into a Google Doc. This data is then manipulated into a daily tracker as below Using data validation to create dropdowns we can easily flick through every clients’ spend and see how this is tracking against expected daily spend. Having such a view enables us to quickly and constantly monitor spend across all accounts, ensuring all clients do not overspend, and bringing our attention to when there are opportunities to increase marketing reach while staying in budget. The set up using Supermetrics for these graphs is easy if you know your way around Excel, and if not, there are a whole range of reporting & managing templates available.We are quite comfortable with Excel and so have developed further automations to save time and help us improve our clients’ accounts even further.

Performance Tracking

While we monitor performance manually & daily to improve accounts’ ROI, we have set up a dashboard to automate alerts based on when performance dips below expected to reduce the risk of human error. One example is bounce rate – if its higher than expected we’re alerted almost instantly to investigate. Recently a page on a client’s site broke causing a higher than expected bounce rate. Notice the spike on tis graph: With this functionality, if someone is away or something slips through the net, we can still instantly identify and fix the issue. Our client was grateful, not only for the notification of a broken page, but also lack of dip in account performance. Conversely, if performance is better than expected, we are alerted so we can act and try to find ways to make the most of the improved performance.

SEO Performance

Yes, there is plenty of SEO reporting software available, however a custom report using data pulled in from SEM Rush allows us to show what matters to our clients; results. Furthermore, we can easily show accurate year on year data thanks to the clever date selector when building a query. This information is key to showing benefits of SEO work over time. It also allows us to look at overall industry trends and seasonality that may impact account performance – especially in the travel industry! Moreover, Supermetrics allows us to have both PPC & SEO data in a single view for the client, this is useful for establishing the results of our work across different work streams. One key use of this functionality is to display visibility of keywords targeted in both SEO & Adwords, allowing our clients to easily manage their search engine visibility and track our performance.

In Depth Analysis

Being able to quickly pull Adwords data from several accounts at once, and filter and segment as required, enables us to regularly and often provide interesting statistics on account performance, that in turn help us improve the account’s performance. For example, one client runs 7 different Adwords accounts each targeting most countries in the world. We wanted to look at how different markets perform overall for the client against a few metrics. Setting up a query and getting the data we needed for this took all of 5 mins, without Supermetrics it could have easily taken an hour. The analysis found useful insights into which markets performed well and which less so, allowing us to quickly make bid adjustments which improved account performance. This shows how Supermetrics allows us to perform in depth analysis for all our clients, and most importantly, much more frequently than if we did not have it.


As a small yet fast growing PPC & SEO agency, using Supermetrics allows us provide a level of service and analysis clients would expect of a larger (and more expensive) agency. On top of that, with innovative applications of the software, we know our analysis and service can go beyond those agencies. It’s thanks to the software’s flexibility and frequent updates that we can do that.

About Sam Martin-Ross

Having worked at Forward3D on accounts such as Ralph Lauren & Tommy Hilfiger, then moving to onefinestay and working on their £4m yearly budget, Sam set up his own agency. He saw a way to provide industry leading, best practice PPC & SEO work and service cost effectively. Sam enjoys seeing the direct impact our work has on his clients, and is constantly looking for ways to make Digital Uncut more efficient so that it can continually provide better service and results.

Analyze Your User ‘s Behavior In Depth: Cohort Analysis

COHORT ANALYSIS • 6 – MINUTE READ • by Sumi Goonetilleke on January 2 2017

Do users really engage with your content? Use the right tool to find out!

You often publish articles, run a campaign or post news worthy blog posts but you don’t really know how your readers engaged with the article or how often they shared your article. You might be measuring this by analysing scroll-depth, the bounce rate or time spent on the page etc.

But that won’t give you the complete picture. In this article, I am going to show you an extremely valuable dimension that most people do not use that often. Cohort analysis in Google analytics is the tool you should use to analyse user behaviour over a short period of time.

A cohort is a set of users who have a similar interest or behaviour. The Google analytics cohort report provides only one type of a cohort which includes all users categorised according to the date they arrived. The data that Google considers in this report is really the day that the user started the first session. Therefore, in this beta version of cohort analysis Google only gives us one Cohort type (common attribute) and it is the acquisition date.

You can find this report in Google analytics as below. Audience- Cohort Analysis. cohort analysis

Let’s try to understand the cohort report first. See the places marked in dotted lines on this diagram. These are the three main sections of this report. Tools at the top helps us to create the Graph and the tabular data in the data section.

Try Cohort Analysis Template and many other templates from Supermetrics Google Sheet Add-On’s Template Gallery. If you do not have Supermetrics yet, you can try it for free for 30 days by clicking the button below


How to make the report?

There are four main fields that helps us generate the report. Cohort type, Cohort size Metric and Date Range.

What is your Cohort?

This is the basis of the cohort. This cohort type corresponds to the table column which includes the total number of users in the cohort. In this beta version Google only provides one dimension, and it is the Acquisition date (or we can call it the users first session). Hopefully Google will come up with other cohort types very soon.

How big is your Cohort?

This is the time frame you want to select when looking at the cohort type. This cohort size corresponds to the cell which includes the date and the total number of users in the cohort.
    • By day – If you select this, it means that you want to see all users acquired on a specific day.
    • By week – This means that you want to see the users acquired within the whole week. (Or a period of seven days)
    • By month – Same as above, you want to see the users acquired within a specific month.
In summary, Google grouped users in three separate (cohorts) groups. User’s first interaction on a particular day. User’s first interaction within the specified week, and User’s first interaction within a specified month. Once you select a Cohort size, the next thing is the “metric” that you want to look into.

What do you want to measure?

This will be specific to the actual data you will be seeing in the report. You can select aggregated metrics per user, User Retention or Total goal completions etc. You can only select one metric at a time. Metric corresponds to all columns in the table other than the first column which shows cohort type. The analysis technique is to look into a specific metric for a specific cohort to understand how that metric performs over time.

What date range do you want to analyse?

This is the time range for the data that appears in the table. This corresponds to the number of Rows in the table. If you select 7 days there will be 8 rows including the row with the totals, and if you select 14 days there will be 15 rows including the row with the totals. If you choose the Date range as “Last 7 days”, then analytics will start to count 7 days from yesterday. And pulled out the data from the past day 7, 6, 5,4,3,2 and 1 (yesterday) Before we start to analyse the data using the cohort analysis tool we need to know the data laid out in the table. There are 13 columns including day 0. Rows will vary from 8 to 31 as per the 7 day and 30 day reports. In this report, there are 5 colour variations Google use. Darkest represent the highest metric values, and lightest represents the lowest metric. As you can see in the above image, On Dec 5th we had 29,967 users which is 100% on Day 0. But on the next day only 4.93% returned. And then the second day we only had 2.71% returns. By looking at this data we can see how our users are coming back to the website. This way we can see whether our content is interesting enough for our users to come back again and make use of it or they simply drop out.

What can we analyse with Cohort Analysis?

We can use this cohort analysis for a few different types of analysis.

If you are having an e-commerce business. You might see your business doing well on a month to month basis. But when you drilled down to weekly cohort analysis you might find that some days you are not doing well. By digging deeper into this particular day you might find that the marketing activities you did on the day haven’t actually made a good return. So now you know how to improve your marketing effort to boost up your sales by comparing the marketing activity initiated on the day.

You can also look into a “single column” in the cohort analysis report. If you are retaining the same percentage of users across all cohorts on the second day, you know that your website is consistently giving your users a better user experience, or your site speed is relatively okay to keep engaging your user’s consistently. But on the other hand, if you see a steep deterioration of user retention at day 2 then it might indicate your website speed is not up to the level that users prefer or your content is not appealing enough for your users to come back and refer the content.

Remember that the cohort analysis shows user engagement in your website. This is extremely important if you are in the business of trying to engage users in multiple occasions and need to keep them engaged regularly.

And also, the cohort analysis is extremely important for businesses that runs short term campaigns and marketing efforts. Tracking both acquired users and retained users over a period of time will definitely put a smile on your face. Cohort analysis is one of the best ways to make it happen.

You can also add segments to your cohort analysis report. Segmented cohort reports will be displayed in another colour on the cohort analysis page.

I have applied a Segment to my cohort analysis report called “made a purchase” and now I have two reports to compare.

As you can see on the 6th December, 74 new users started the purchasing journey but only 21.62% came back on the next day. On the second day after the First visit only 10.81% of the visitors returned to make a purchase and then it increased on the next day to 14.86%. Then it has plummeted to 1.35% then no one returned to purchase from the visitors who came on the 6th Dec. So, the marketing effort on the 6th Dec only lasted for three days. This way, we can analyse whether our marketing effort has been working in our favour on any particular day.

As you can see, this is an extremely important tool that you can use to make your business improve user retention for every single metric. Having a complete understanding of the user retention will always help you improve your Return on Investment.

Defining the right cohort to give you the right answers to your questions is very important. Using Google Analytics, you can create reports that help you answer this within a few minutes. Imagine that you need to check whether your customers are coming back after their first purchase. How did they first engage with your website? What triggers them to buy from your website? How long did they stay on a page before making a purchase? How many users reached your goals? Have the number of purchases declined over time? How many pages have they visited along the purchase journey? How did the user behave before your promotion and after the promotion? How do different genders act upon your promotional email? What age group was engaged for the longest period of time?

These are all questions that can be answered by creating advanced custom cohort reports. I will be discussing this in the next article so stay tuned!

Five Analytics Tools Every Digital Marketer Should Use

ANALYTICS TOOLS · 6-MINUTE READ · By Paul Koks on December 19, 2016

As a digital marketer you should not limit yourself to one or two analytics tools. Your understanding of your visitors and customers will start to explode once you combine the insights of multiple tools.

A great marketer or analyst understands the value of a wide range of tools instead of just being an expert in tool X.

You don’t have to exactly know how to use all tools on the market; it just makes a big difference if you know which tools are useful and why. In this post I will elaborate on five different Analytics tools that can be a great help to understand your customers and grow your business. Each of them have their value, but if you combine the insights of all tools you will gain so much more. Let’s dive right in!

1. Web Analytics Tools

The first one is a no-brainer. You want to have at least a basic knowledge of digital measurement tools like Google Analytics. Collecting meaningful and accurate quantitative data is the starting point for most companies. Make sure to spend enough time in getting your measurement plan in place. So that the implementation and configuration can be done in a proper way.

Adobe Analytics vs Google Analytics

I often get asked: “which tool is better?” There is no single answer here. The best answer would be:“it depends!” For most companies out there Google Analytics is a great solution. With its free edition and Google Analytics 360 it can serve a large range of businesses. Read this article to learn more about the differences between the free edition and GA 360. You need to have the right people, a great process and suitable tools to get the job done. As a rough guideline:
  • Google Analytics (free edition) is suitable for most online businesses that don’t attract a ton of traffic (more than a million of visitors each month). Or simply don’t have a dedicated team and process for optimization in place yet.
  • Google Analytics 360 is a perfect solution for those companies who have to deal with large amounts of data and run into sampling problems on a weekly basis. In addition these companies should be much higher on the digital ladder than companies who use the free edition. You really have to take Analytics and Optimization seriously if you consider Google Analytics 360. This goes far beyond employing one full-time digital analyst or data scientist.
  • Adobe Analytics can be a pain to set up. But at the same time, it’s so flexible. Especially their ad-hoc analytics module allows you to quickly analyze data sets and apply segments beyond your imagination. If you are in the enterprise world and have both the technical and marketing resources and Google Analytics 360 doesn’t completely fulfill your needs, you can consider Adobe Analytics.
In my experience I have found that most companies don’t use the potential of Adobe Analytics if compared to Google Analytics. In this case I would strongly suggest to stay with Google Analytics 360 as it is most often much easier to implement and less costly. And keep in mind, your tool is worth nothing if you don’t have the people to take advantage of it. Such a simple rule, but so often forgotten!

2. Online Survey Tools

Your web analytics tool is great in collecting information around the What. So that you can easily find out what is happening on your site! Assuming that you are collecting meaningful and accurate data. However, if you don’t collect Voice of Customer (VoC) data you are missing out. I have come across many companies who are overly obsessed with their NPS score.nps-scoreIt’s a proxy in a sense that it gauges the customer’s overall satisfaction with a company’s product or service and the customer’s loyalty to the brand. It’s ok to measure it, but it doesn’t tell that much in my opinion. So in addition I strongly recommend to implement online survey tools to learn more about your website visitors and their desires. I recommend to check out Qualaroo if you are serious about running online surveys. qualaroo Three ways to make online surveys useful:
  • Identify who is visiting your website so that you can better segment and personalize.
  • Identify what people try to accomplish on†your website so that you can better serve them.
  • Get a more holistic overview of your website visitors by supplementing your behavioral data with VoC data.
VoC data is really powerful and you should definitely collect it. Always make sure to only ask questions that are relevant for your visitors and cannot be answered with other data sources without bothering your visitors. You just have to find out how far you can go without negatively influencing the user experience and your business results.

3. CX Analytics Tools

Customer (Experience) Analytics tools can be a great help if you want to get down to the nitty gritty of what’s happening on your site. Typical questions you can get answered by these tools are:
  • Which forms have the highest exit rate?
  • Which fields have the highest amount of re-entries?
  • On which pages are visitors struggling the most?
  • How do visitors behave in the conversion funnel?
  • Do visitors read content below the fold?
  • Do visitors actually see the call-to-actions on this page?
These tools typically come with the option to track all behavior of every visitor on your website. By aggregating the data and using built-in algorithms it is possible to identify on which areas on your website you need to improve. I strongly recommend to watch this Advanced Funnel Analysis video by Gary Angel if you have a specific interest in form and funnel optimization:
The beauty is that both online survey tools as well as CX Analytics tools can be flawlessly integrated with your web analytics tool. By doing this you can retrieve the most insights from your data. There are quite a few vendors in this market. Here are three suggestions for tools in this category:

4. Landing Page Building Tools

According to Hubspot research, the typical landing page converts at 5 to 15%. The three main reasons that digital marketers are resistant to using landing pages in appropriate situations:
  • They take too long to create or are too difficult to create
  • They’ve never been able to achieve incredible conversion rates in the past
  • They don’t know how to systematically improve their landing pages
Lucky you, all three of these problems can be solved with tools. Landing pages are a great help in customizing the experience of a subset of users. You can use a ton of different landing pages that best match your customer segments. Based on my own experience, I recommend to check out these two tools:

1. Unbounce

One of the leading landing page creation tools is Unbounce. The name suggest that visitors to their landing pages don’t bounce but convert. This tool is very simple to use because of its “drag and drop” interface. Some more features will you like:
  • 100% mobile responsive
  • Publish to any domain
  • Easily add any script, without needing IT resources
  • Drive conversions with overlays
  • Match your branding
Make sure to check out whether Unbounce might be the right fit for you.


On my own website I have integrated Leadpages in the conversion funnel and with great success. For less than $50 per month you can built an unlimited number of landing pages. They cannot only be used†as landing pages, but also as “normal” pages on your main domain or any other domain you prefer. The beauty is that you can literally set them up in minutes because there are so many templates available. I really hope these tools lessen your dependence on IT and get you ready to deploy high converting (landing) pages in the near future!

5. A/B Testing Tools

The last, but unmissable piece of the puzzle consists of A/B Testing Tools. Controlled experiments are one of the best ways to actually test all the quantitative and qualitative data and assumptions you have collected with all tools mentioned before. Simply changing your website pages and structure based on the What and the Why is something you shouldn’t do. Running controlled experiments will help you to find out How you can offer the best user experience based on a valid test. There are many†tools on the market that you could use for running your A/B tests. Optimizely or deploying your tests via Google Tag Manager (for free) are both a great choice. I have in particular good experience with running A/B tests via Google Tag Manager. You can either use events or custom dimensions to capture your test variations. Segmenting your test results is one of the best strategies to learn what works and for what audience. custom-report-device-category-level-1024x769 The ideal situation would be when you can feed your Google Analytics account with the test results. Read this article to learn more about integrating GTM tests with GA data. Hope you have picked up a few great new ideas here. What other type of tools would you recommend to add to this list?

About Paul Koks

Paul Koks Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

Monitoring AdWords’ Campaigns: 7 Tips To avoid Under- and Overspending

ADWORDS’ CAMPAIGN MONITORING · 6-MINUTE READ · By Tina Arnoldi on December 12 2016.

With bid strategies and automated rules (in Google AdWords), you do not have to manually monitor every account every day. These are valuable tools for marketers who have multiple paid accounts. Setting some basic rules is a big time saver.

However, it is still important to know how to manually monitor a paid budget to keep costs under control. Below are three steps to address underspending in your paid account and four steps to address overspending. Even if you represent a large shop where tens of thousands of dollars are spent each month, understanding these budgeting strategies will help you get the best return for your dollars.

Prevent underspending – Ad spend bids

Spending less than your daily budget is not necessarily a good thing. If you have run paid campaigns for a while and continue running them because of a positive return, then you want to reach the daily budget you set up in your account. Underspending may happen if you choose a bid option of Target and Bid instead of Bid only.

With Target and Bid, you restrict ads to a specific targeting method. If that criteria is not met, the ads will not show. With Bid only, you are not restricted to the selected targeting method. With a group that is underspending, change the bid type to Bid only.


Prevent underspending – Share a budget

Some campaigns may not be hitting their targeted daily budget because of settings at the campaign level. If that occurs in AdWords, consider the Shared Budget tool which does exactly that – it shares a budget across campaigns.

With a shared budget, you are more strategic about your spend so your high performing campaigns receive the most budget, yet your under performing campaigns are not completely ignored. This provides a chance for those poor performing campaigns to do better and potentially earn more of the daily budget over time if you decide to reallocate the budget at a later date. (This feature is also available in Bing.) However, this is not recommended with a test campaign since your goal is to have enough data to determine if certain ad groups or keywords should be allocated a higher spend threshold.


Prevent underspending – Accelerated Delivery

The recommended setting in AdWords for your ad delivery method is Standard: Optimize delivery of ads, spending budget evenly over time. And the rationale for that makes sense. Accelerated ads could result in lost traffic at the end of the day.

But Standard delivery could result in your budget not reaching the daily spend. If you are not spending your full budget, change your delivery method to Accelerated. With this setting, Google will enter your ad into all eligible ad auctions until your budget is spent for the day.


Prevent underspending – Disapproved Keywords

If you have a very tightly themed campaign with only a few words and some of them are disapproved, your ads will show less often and you may not reach your daily spend. When you first create a new ad group, set up an automated rule so you receive a notification if a keyword is not triggering your ads. A keyword is disapproved for AdWords when it violates one of Google’s policies. If you disagree with the reason for disapproval, it’s worth calling support or submitting a support case stating your case for why your keyword should be allowed to run.


Prevent Overspending – Monitor placement performance

Whether you use automatic or manual placements, it is very tempting to set it and forget it. Even though a site may seem relevant to your campaign, it does not mean that it is relevant. Compare the performance of your different placements to determine if there are some you should exclude.

If a particular site in your placement report costs a lot of money compared to other sites, meaning visitors click but never convert, that is a good indicator a site may need to be excluded. You should also look for irrelevant URLs. I frequently find automatic placements in accounts that are not at all relevant to the client’s offering even though the general targeting method indicated a site was relevant. If it is not clear what a URL is about, simply copy and paste it into your browser to view the site. From there, use your first impression when evaluating whether a placement should stay in your campaign. If the site is relevant topic-wise, but the site is poorly designed or looks spammy you may not want your brand on there.


Prevent overspending – Poor quality keywords

With an automated bidding rule, you can automatically increase your bid every time a keyword falls below the first page.


But before you automate this, you want to ensure it is worth spending more money on your keywords. Start by reviewing keywords that have a low CTR (click-through-rate) since this affects your quality score (QS) for keywords. A low CTR impacts how often your paid ad is shown and you could be charged more when it is shown.

You also want to check the Search Lost IS (rank) for your keywords. For example, a rating of 50% means that in half of customer searches that could trigger your keywords, the ad was not shown because of ad rank or because you were outbid by a competitor. Check if the keyword in question is profitable before deciding whether to bump this up to the first page rather than making a quick decision to beat a competitor no matter what. If a keyword not giving you enough of a return for what it will cost you, you may want to pause it instead. Or you could create a new, more relevant ad group with a specific landing page to increase the quality instead of the spend.

The Search Lost IS (budget) is another good number to check because it tells you if you are running out of budget. If this number is 50%, it indicates you are running out of budget halfway through your daily. Here too, you want to look at the data collected so far before making a decision about increasing the budget.


Prevent overspending – Ad Position

“I want to be #1 on Google”. Whether it’s organic or paid, everyone wants to be the top result on Google since many people never make it to page two. But does it really matter if your paid ad is #1? This is where conversion data is especially valuable. You do not want to use a bid strategy for the top of the search results if it doesn’t provide a return. An Adobe Media Optimizer study indicated that paid ads in the 4th position may have the best results. Remember to look at this in light of your data. Bid strategies are a very useful part of AdWords but gather data before you use a strategy, especially when it comes to targeting the search page location.


Prevent overspending – Check device type

There could be costly conversions in your account which result in you spending money for conversions with a poor ROI. Your best conversions may happen on a mobile device but you do not know that until you look at the Attribution report in AdWords.


To specifically view conversions by device type, choose Cross-Device Activity on the left hand site in the Attribution section.


Your Devices report shows how visitors used their devices before converting. They may switch back and forth with their tablet, mobile and desktop device before finally converting.

If a device type is not frequently used to reach a conversion, it does not mean you should completely exclude that device type because usage may change over time. For example, if you discover that Tablets with full browsers have few conversions or conversions that add little to your bottom line, you can set a bid adjustment to slightly decrease the amount spent on tablets. As a result, your budget will be better spent on the devices that provide the best return.


Both overspending and underspending can be problems with your paid accounts. Even with all the automated tools available, there are still some manual things you should pay attention to in your accounts. To recap, if underspending is an issue, check the bid settings for your ad groups on the Display Network, consider sharing a budget across campaigns, and use accelerated delivery. Although you technically can’t overspend for the month when you have a daily budget, you can overspend on ads that do not product results.

If that type of overspending occurs, check your placements to see if they are quality ones for your business, stay alert for poor quality keywords, monitor ad position, and check your device type. None of these changes are complicated when it comes to managing a PPC budget and minor tweaks can make a big difference in your account.

And if you are managing budget and bid data for multiple accounts, consider using the Client Budget Tracker & Alert, which makes it easy to view these moving parts on one screen. This reporting template will help you avoid under- and over- spending by showing what percentage of budget was spent. You can also monitor the allocated budget, budget spent, daily spend and budget projection on the chart for each of your clients.

About Tina Arnoldi

???????????????????????????????????? Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

Successful Holiday Campaigns: The Most Important Metrics To Analyze

HOLIDAY CAMPAIGNS’ METRICS · 6-MINUTE READ · By Misty Faucheux on December 5 2016.
The holidays are here, and nearly every company is ramping up their marketing efforts to try and gain new customers – or encourage current customers to purchase again. With so much competition and higher CPCs and CPAs, marketers must use every available instrument to ensure success. Reporting and analytics must be a part of that toolkit.

How to Monitor Your Campaigns Throughout the Holiday

Real-time metrics provide you with a snapshot of how your campaign is performing at a certain moment in time. For example, you can monitor the days leading up to Christmas to determine how well sales are doing. Google Analytics now offers real-time metrics to help you determine the success of your campaign, including being able to compare cost versus total revenue garnered.

Other real-time metric tools include Clicky, KISSmetrics, GoSquared, Piwik and many others. Always compare platforms and determine your actual needs before using them. Prices will vary with platforms, ranging from free to a minimum monthly fee to potentially thousands of dollars.

What Metrics Should You Be Monitoring?

Depending on the type of business that you have, you will need to monitor different metrics. For a physical store, you will probably be more interested in coupon downloads and phone calls over number of impressions. If you have an online store, you will want to measure clicks, click-through rate and sales. Any retailer will also be interested in conversion rate and CPA, and how that contributes to overall ROI. Always determine what metrics you are most interested in before launching a campaign.

The channels that you use will also vary. Most B2B companies will focus on LinkedIn, Search and Display. Many B2C companies, on the other hand, may focus more budget on Twitter and Facebook with a mix of Search and Display. This means that the metrics that you have measuring will be slightly different based on platform. For example, in AdWords a lead is a conversion, but with Facebook lead form ads, it’s a form fill out. While these mean virtually the same, the terminology is slightly different.

Ongoing Metrics

You’ll have to be constantly tweaking your campaigns throughout the holiday season. Metrics that you should always pay attention to include the following:


If you find that you’re running out of budget quickly or not really getting clicks, then your budget probably isn’t high enough. Increase budget as needed, but constantly compare it to ROI. If you are blowing your budget, yet are only receiving a minimal number of conversions, then the campaign might not be worth running – or it needs serious adjustment.

Everyone wants to do something during the holidays, but many businesses find that it’s not worth the expense. For example, many B2B companies don’t have a ton of success during the holidays since their targets are typically winding down for the year or are out of budget. Always consider your goals before launching a holiday campaign. Know what your target conversion rate and CPA are. If a holiday campaign isn’t contributing to that, hold your budget for another time of year.

Keyword Bids

You’ll notice that you may be getting a lot “bid not high enough” type of warnings. Keyword costs tend to quickly escalate especially on important keywords like “black Friday” or “specials”. Adjust bids higher, and even consider doing bid adjustments, especially on days when you expect your audience will be online.

Also, review low-performing ads. Consider lowering budget on these, or even shutting them off.

Typically, you want to increase your bids by at least 10% to 20%. For example, in a recent campaign for a client, we noticed that most conversions were happening Tuesday night through Thursday morning. We increased the bids by 20% during these key timeframes and saw conversions increase by 5% after doing this.

To set bid adjustments in AdWords, go to Ad Schedule, and then Select Bid Adjustment. Then, increase or decrease your bid adjustment.


Impressions/Impression Share

Impressions and impression share often decrease as competition increases. If you notice a significant reduction in impressions, review your impression share in comparison to previous months. Impression share is the number of impressions divided by total eligible impressions. If it is significantly lower because of seasonal competition, increase budget, and then monitor results.

If impression share drops below 50%, review your keyword bids. If they’re too low, try increasing them by about 20%, and then monitor over the next few days to a week to see if impression share improves. You might have to also increase your overall budget. When you run out of budget, your ads will stop displaying, reducing the number of impressions. You should also experiment with changing geo-targeting settings to narrow your target area as well as improve the quality of your ads.

CTR, CVR and CPA Per Ad

Overall CTR, CVR and CPA will tell you how your total campaign is doing. Yet, diving down into the individual metrics of each ad will help you ascertain whether certain ads are performing better than others. An ad might be driving a lot of clicks, but not converting at all. Another ad, however, might be converting, but at a significantly higher cost than the others. Understanding these metrics in relation to the ads helps you determine best-performing messaging and imagery. Then, you can turn off budget-wasting ads, and create new ads similar to your higher performers.

A decent CTR is 2%, and a good CVR is between 2% and 5%. If your ads aren’t performing well, consider changing messaging. If the larger problem is a lack of brand awareness, you will need to add additional tactics to the mix to assist with this, i.e. a social media or PR campaign to help visitors recognize the brand. CPA is going to be dependent on your product or service. For example, a B2B company may be willing to pay over $200 CPA for a lead if that means thousands of dollars in business. Yet, a small retailer will only be willing to pay $20 a lead since the average sale is $45. Your CPA shouldn’t be more than half of your average sale since this amount doesn’t even include other advertising costs, i.e. paying a DMP or vendor to do the work. If CPA is too high, lower target CPA bids. This might reduce your overall conversions, but you don’t want to spend more than you make. Review keywords and ads, and turn off any poor-performing, high CPA ones.

Bounce Rate

While organic search practitioners cling to bounce rate, oftentimes paid search managers forget about it. A high bounce rate indicates that there is a disconnect somewhere, i.e. keyword and ad, or ad and landing page. Always pay attention to this, and adjust any ad or keyword contributing to bounce rate. Not only does it negatively affect quality score, it’s a waste of budget.

If bounce rate is above 75% for paid search, review your ads and landing pages, and ensure that their language is similar. Don’t offer free shipping, and never mention it on the landing page. Once you adjust messaging, test and monitor over the next week or so to see if bounce rate drops.

Create a Post-Campaign Report

Once everything is said and done, create a post-campaign report showing the above metrics over time and how well the overall campaign performed. Point out learnings, what worked, what didn’t and opportunities for future campaigns. Incorporate year-over-year results to help with future planning and forecasting.


Holiday campaigns are usually expensive, but that doesn’t mean that they’re ineffective. In fact, many retailers make a large percentage of their sales during this time of year. You must, however, constantly monitor important metrics and adjust as needed. Make your end-of-year campaigns successful by planning ahead and seeing what worked in the past. Then, leverage those past insights in conjunction with current analytics to help pivot throughout the season.

About Misty Faucheux

20140725_0031 Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

Why Your Conversion Rate is Wrong and How to Fix it

CONVERSION RATE · 6-MINUTE READ · By Paul Koks on November 28 2016
The conversion rate is one of the most common metrics that companies rely on when they optimize their business. But how do you actually measure it; can you trust your numbers?

We all have our own set of favorite metrics that we set targets for and try to optimize along the way. In general, the most important metrics that can directly be tied to increasing revenue and margin or reducing costs are often called KPIs.

What are your KPIs? I bet a metric closely related to conversion rate or conversion rate itself is on your list.

In this article I will explore the conversion rate metric and uncover why it is fundamentally wrong and what to do about it. As most of you will be familiar with Google Analytics, I will use this tool and the Google Analytics Demo Account to illustrate things in more depth.

Default Goal Conversion Rate

When asking people about their conversion rate, they often refer me to this report: (Conversions >> Goals >> Overview)   overall-goal-conversion-rate   The overall goal conversion rate number is based on:
  • All different goals that are set up in your Google Analytics account.
  • All sessions that drove traffic to your website.
So on default your goal conversion rate can also be calculated as: (Total Number of Goal Completions / Total Number of Sessions) * 100%. This means that if you set up five different goals and a visitor completed them all within one session, the goal conversion rate of that session would equal 500%. Let’s break it down a bit further here.

Overall Goal Conversion Rate

In every Google Analytics view you have the option to set up twenty different goals divided in four goal sets. Here is a simple rule to keep in mind: “The more different and easy to achieve goals you set up in your view, the more skewed your overall conversion rate metric will be.” Google Analytics allows you to set up four different goal types:   google-analytics-goal-types You have to be very cautious when implementing duration and pages per session goals. These type of goals can skyrocket your overall goal conversion rate and make it a useless metric. In my opinion you should only set up goals for micro and macro conversions that are closely related to your bottom line. Keep a separate view if you want to measure easy-to-achieve goals as well.  

Fix #1: Apply Segments Instead of Engagement Goals

Context is key so I understand when you still want to examine the effect of a higher or lower duration and pages per session on your most important conversions. This is where segments become your best friend. Segments allow you to exactly replicate the effect of the implementation of engagement goals. It might be a bit more difficult to work with them at first, but it’s definitely worth it.

Duration Segment

Here is an example setup of an engagement goal: session duration is longer than 60 seconds.   session-longer-than-60-seconds   You can apply this segment to your data view to find out whether people that spend an x amount of time on your site convert better or worse than others. Be cautious because time based metrics are easily misunderstood.

Pages/Session Segment

Within the advanced section of segmentation you can apply pages per session segments as well. Here is an example:   pages-seen-more-than-3   In addition you can apply multiple conditions to set up a segment.

Segment with Multiple Conditions

Let’s assume you want to segment on sessions with a duration time of longer than three minutes and more than five pages seen. Here is the outcome of this multi-conditional segment : multiconditional-segment   Segments are very powerful and really come in handy when analyzing conversion rate metrics. Make sure to leverage them for your business.

Fix #2: Exclude Known Traffic

You want to filter out your own traffic in addition to only setting up goals for your most important conversions. You conversion rate metrics will remain skewed if you refrain from doing so. The larger your portion of traffic relatively is, the more skewed your data will become. Setting up IP address filters can easily be done. Here is an example (based on regular expression):   exclude-ip-address-filter   There is a great tool that might come in handy if you need to filter a range of IP addresses instead. In some cases you have to deal with a dynamic IP address which can’t (easily) be filtered in Google Analytics. Two suggested workarounds for dealing with dynamic IP address filters:
  • Filter your behavior on a unique dimension; in many cases city might do. (preferably set as a filter instead of segment)
  • Block Google Analytics cookies via Ghostery.
Read this article if you want to learn more about useful Google Analytics filters. Please make sure to always keep an unfiltered, raw data view that doesn’t contain any filter at all. This is your “rescue” view for when things go wrong.  

Fix #3: Include Only Your Target Market

Many companies do only business in specific areas in the world. Here is a good example of the Google Analytics Demo Account:   ga-demo-account-target-market-1   42% of the sessions reside from Northern America.   ga-demo-account-target-market-2 This region is responsible for 96% of the revenue and 98% of the transactions. I can definitely conclude here that the United States (and Canada) is their main target market. In this case you should set up a separate view for your target countries. Here is an example of a country filter in Google Analytics:   google-analytics-country-filter   I recommend to first set up a segment before applying a filter to your view. Experimenting with segments allows you to determine the effects without permanently affecting your data set. Another option would be to apply your filters to a testing view first.

Fix #4: Exclude Specific Customers

This fix only applies if you have one unique offer (product or service) that people can only buy once. You might want to exclude this group in one of your views to get the most accurate goal conversion rate. You could work with custom dimensions to identify and exclude this group. However, make sure to experiment with segments instead of filters if you aren’t 100% convinced about how to set this up. It can be really complicated for sure!

Fix #5: User Level Conversion Rate

There is no right or wrong here. Conversions can be measured based on a user or session level in Google Analytics. Some analysts argue that a session based metric is better because a session represents a unique opportunity to convert, where the user based metric could include more than one session. Others (including me) strongly believe in user based metrics, because it often takes more than one session to convert a user on her journey and you will get a more accurate picture of what’s going on if you analyze them both. Calculated metrics can help you to set up a user based conversion metric in Google Analytics. In this example we examine the Google Analytics Demo Account. This is how to set up the E-commerce conversion rate per user metric:   conversion-rate-per-user The next step could be to use this new metric (Conv Rate Per User) in a custom report. For demonstration purposes I have modified the channel report to include this new metric:   conversion-rate-custom-report   So now you have access to both metrics in one report. The user level conversion rate is usually 20 to 25% higher than the session level conversion rate. However, this is just a simple benchmark based on my experience, but it might greatly differ in your situation. Note: calculated metrics work retroactively on your data set. This allows you to discover some great insights on historical and future data! Keep in mind that cookie deletion, multi-platform and browser experiences can greatly influence the user level conversion rate metric.  

Fix #6: Segment on Specific Sources

In order to make any metric really useful, you need to segment it. An average conversion rate of 2% doesn’t tell much. The real insights are hidden in the differences between each of your segments. This could be new vs. returning visitors or mobile vs. desktop visitors. One of the other very useful cases is segmenting on the channel level. You will often find that a few of your channels bring in almost all conversions. You should either concentrate on your most important sources or improve the least performing onces. Read this article about segmentation tips to get started right away! Just always segment your data to answer important business questions in your organization.  

Concluding Remarks

  • The conversion rate metric is one of the metrics to keep an eye on, but there are other important ones for your business.
  • Only set up goals for your most important metrics if you want to use the overall goal conversion rate metric for optimization purposes.
  • Apply the suggested fixes in this article to make the most sense of this metric.
  • Supplement these ideas so that it best reflects your unique situation.
  • Use both a session based metric and calculated user based conversion rate metric to learn the most about visitor behavior.
Well, this is it from my side. I hope you have picked up a few ideas in this article! I am happy to hear your thoughts! How do you use the conversion rate metric as part of your optimization efforts?  

About Paul Koks

Paul KoksPaul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.  

New Bing Ads: Campaign Creation Workflow and Expanded Text Ads

BING ADS NEW USER INTERFACE · 5-MINUTE READ · By Misty Faucheux on November 21 2016.

Bing Ads has taken steps to better compete against AdWords and similar platforms. Microsoft has released a new version of the campaign creation workflow. The goal of this update is to make it easier for marketers to create effective campaigns. On the heels of this update, Bing Ads now offers Expanded Text Ads similar AdWords’ new ads. This post will guide you through the new workflow as well as how to use the new text ads.

Overall, Bing Ads has been trying to make their platform more valuable for marketers. Over the past year or so, they’ve added new bidding options, targeting and ad extensions. They’ve even made their platform a bit faster to reduce lag time and frustration. These latest updates are simply their next move to improve usability.

Creating Goals

When you launch the new workflow, you’ll notice that you now have the option to select a marketing goal for your campaign. Anyone who has used Facebook’s or Google’s ad platforms should recognize this type of setup. image1No matter which goal you choose, you’ll still have access to all the available features.

While many may gloss over this section, it’s worth thinking about what your actual goals are. Some will be obvious. For example, if you want to send visitors to gated content, then Visits to my website is the logical choice.

Yet, you may have to think a little harder if – for example – you’re advertising a brick-and-mortar location. If a local dentist wants someone to call for an appointment, then phone calls will be the most important goal. Yet, another local business like a retailer may want people to come to the location. Phone calls would be less important in this case.

This screen also provides you with the option of importing a file or uploading your AdWords campaigns. If you haven’t done your keyword research, do it now. You’ll need this data for the rest of the campaign setup. You don’t want to simply target random keywords without doing adequate research to determine competition, search volume and relevancy. Selecting the right keywords require some thought and research.

Campaign Settings

The campaign settings are fairly standard. You must add a campaign name, budget, language and location. What’s different from previous versions is that you can now add radius targeting from this screen and copy settings from other campaigns.

image2 When copying campaign settings, always review what has been imported before going any further. For example, you want to have the same budget and language, but for this campaign, you only want to target Boston as opposed to all the United States. It’s worth taking a second to review before moving forward to avoid mistakes.

When ready to go to the next screen, hit Save & go to the next step.

Ad Groups & Keywords

In this screen, you’ll add your ads and keywords. Here’s where your previous keyword research becomes a necessity. If you didn’t do it beforehand, you can obtain keyword suggestions. This will provide information similar to standard keyword research, but won’t be as in-depth as if you would have performed your keyword due diligence. image3 You will see search volume, cost and competitiveness, and the tool will group keywords into ad groups. Typically, you only receive a few keyword suggestions per category, meaning you may miss some niche keywords that would better fit your goals and targets. You can search for suggestions by keywords, service, products or website URL.

Once you select your keywords and ad groups, select Save & go to the next step.

One tip: If you are interrupted during campaign creation, simply select Save & exit. Bing Ads will save your campaign, allowing you to pick up where you stopped. Further, if you ever need to change something on a previous screen, click Back.

Ads & Ad Extensions

Now, it’s time to start creating your ads. As mentioned, Bing Ads recently released new Expanded Text Ads. image4 Unlike standard text ads, these new ads have two headlines (30 characters each and separated by a hyphen) and a single ad description up to 80 characters. The standard text ads only had one ad title (25 characters max), and the ad description was limited to 71 characters. image5 The other difference between the two is the Display URL. In the past, this was limited to 35 characters, and you had to manually enter it. Now, the domain and subdomain are automatically generated from the final URL. You also have the option of adding two URL paths. These paths allow you to highlight key offers, products, services or keywords in the URL. According to Bing Ads, the most effective way to take advantage of the Expanded Text Ads is to:
  • Leverage current campaigns and ad groups so you can use current ad extensions.
  • Perform A/B testing with the new ads to try different CTAs.
  • Review high-performing standard ads, and use some of that copy in the new ads.
In this screen, you can also add ad extensions. It is highly recommended that you take advantage of this option. Ad extensions are proven to improve visibility and increase clicks since they offer a way for users to learn more about your business or offer. image6 Plus, you can add information like location or phone number, allowing a user to easily find or call your business. image7

Budgets & Bids

The final step in the process is setting your budget, bid strategy and individual ad group bids. image8 It’s best to experiment with different bids and bid strategies. Some ad groups may require higher bids due to competitiveness or cost. With the Advanced campaign settings, you can also adjust bids based on location, day or device. image9 For example, if you sell an app and most of your downloads occur on the weekends, then you might want to increase your bids on Saturday and Sunday, and decrease bids during the week. image10The same goes for devices. If most of your conversions happen on mobile, you can decrease bids on desktop and increase bids on tablet and smartphones. image11


While the new campaign workflow makes it easier to create campaigns, this doesn’t mean that you still don’t have to do your due diligence. Create your goals, do your keyword research ahead of time, and think about what messaging will be most effective with your audience. Leverage the new Expanded Text Ads to focus ad copy and incorporate keywords.

Once you have all this in place, then the campaign creation process will go even faster for you. Plus, it increases your chances of success. Finally, always and consistently monitor and tweak campaigns based on results for maximum effectiveness.

About Misty Faucheux

20140725_0031 Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

How to Discover a Ton of Insights in Three Simple Google Analytics Segments

GOOGLE ANALYTICS SEGMENTS · 6-MINUTE READ · By Paul Koks on November 14 2016
The truth lies far beneath the surface. What I mean here is that you really have to dig deep in your data to find the golden nuggets. I always get a bad feeling when people talk about average bounce rate or average conversion rate. These numbers don’t say much; you are getting somewhere if you can relate them to a certain segment. In this post I will reveal three powerful segments in Google Analytics and how you can use them to increase the ROI of your analysis and business. For training purposes, I will use the Google Analytics Demo Account so that you can easily follow along.

Segment 1: Device Category

A few weeks ago I was approached by the owner of a mid-sized e-commerce store. He had just finished his first analysis in Google Analytics. This was his conclusive statement: “All my visitors are leaving the website on the cart page, so I really need to optimize this page.” After a short chat on Skype it turned out that he didn’t do any segmentation at all. It’s usually the case that a certain group of visitors is performing well and a different group is performing less. After investigating it further, I could simply conclude that the cart page wasn’t optimized for mobile visitors. Both the data and my on-site experience clearly pointed in that direction. Learning: you can’t ignore the device and intent of your visitor when trying to optimize the ROI of your business.

Device Type – Overall Report

Let’s look into an example. Here is the standard “device type” report, focus on behavioral and conversion metrics of Google Merchandise Store: segment-device-category The results indicate that:
  • Desktop is by far the largest segment and tablet is very small.
  • Most metrics are in the same range for the different devices, a few exceptions:
    • Visitors consume relatively a lot of pages and stay longer on the site on tablet devices.
    • E-commerce conversion rate is dramatically low on mobile devices.
You can imagine what would happen if you make an aggregated analysis and take it from there. One out of six visitors arrive on the site via a mobile device and they convert four times as bad as on desktop. That’s huge! This is a great start, but you should want to dive a lot deeper.

Device Type – Segmenting Your Audience

ecommerce-cr-per-deviceI have selected three segments here. Please note that both the “mobile traffic” and “tablet traffic” segment are available in the “system segments” section. You have to create the “desktop traffic” segment by yourself. I recommend to save this desktop segment to all the views you have access to!   desktop-segment-all-views   Selecting six months of data makes it more easy to spot trends:   ecommerce-cr-per-device-six-monthsAs you can see, the tablet Conversion Rate in August was very high compared to earlier this year. This is one of the powerful ways to derive powerful insights directly in Google Analytics. In addition you can use these segments in almost any report (funnels are the exception) in Google Analytics. A more advanced analysis could look like this:   ecommerce-cr-per-device-content-group Here is how I created this view:
  • Select the three segments Desktop, Mobile and Tablet.
  • Navigate to “landing page” report (Behavior >> Site Content >> Landing Pages).
  • Select “Landing Content Group” Product Categories.
  • Filter out (not set) entrances via Advanced Filter.
The data reveals:
  • Key metrics for visitors that enter your site on a product category page, their behavior and conversion rate.
  • The percentage of entrances for each of your categories and the conversion rate (including other stats) per device.
These insights are a great help in understanding visitor behavior per device. So once again, overall numbers are ok as a first start. However, you need to make sure to further segment your data and dig deeper. Aggregating your different pages in content groups can be tremendously useful.

Next Step

Unfortunately Google Analytics doesn’t record cross device behavior on default (user ID implementation is required).   device-overlap-analysis The Device Overlap report shown above is very interesting and helps to find out whether non-converting mobile visitors convert on desktop (or tablet) later. In addition I recommend to run a survey to find out how many devices are used by visitors (that buy) on your site. So you can get a better idea about the purchase journey on your website and how many devices are used. These insights are very useful for setting up and intepreting (A/B) tests later! In short, there is a ton of insight to be gained if you ask yourself the right questions and use the data in a smarter way.

Segment 2: Geography

This segment is very useful if you run an international business or help clients that do business internationally. Navigate to the Location report (Audience >> Geo >> Location) first.   location-report-google-analytics   At a glance you can see that:
  • 90% of the transactions come from the US; conversion rate is far above “average”.
  • Canada is the second country in the top 10 based on e-commerce conversion rate.
  • Most other countries do zero or near zero sales.
Let’s assume Google would hire me to optimize their e-commerce conversion rate. There are two actions I need to take first:
  1. Find out the reasons why these other countries send so much non-converting traffic. Is it because of shipping legislations (only to US?) or other reasons?
  2. Set up a segment that only includes US (and maybe Canadian and/or some other countries) traffic so that my conversion rate is a valid number to try to further optimize.
It’s really important to address these international segments to find out in which countries people convert and where they don’t. Other reasons include, but are not limited to:
  • Cultural barriers / reasons to not buy your product.
  • Language issues; do you need a German, Spanish etc. version of your site?
  • Budget reasons; are your products too high priced for certain markets/countries?
Analyzing and optimizing goes far beyond understanding the simple working of segments in Google Analytics. It’s very useful to have strong analytics skills, but it’s not enough. Educating yourself on how to tell stories with data is very important as well to that you can better convey your message. Start with combining quantitative and qualitative data and do some background analysis as well!

Segment 3: Visitor Type

You might have heard people saying: “The new visitor report information is not completely accurate, because of…”. And I can only agree with that. The numbers are less accurate than they used to be. One of major reasons is that visitors use multiple devices and browsers to access your site. And the number of different devices used keeps on growing. Here is the data for one of my websites (segment = direct traffic):   new-sessions-direct-traffic   In a period of two years, you can see a steady climb in new session percentage. You will probably find similar numbers in your account if you make this visualization based on your numbers. Why is it still useful then? Data analysis is all about trends, analyzing historical data and predicting the future. We still know how specific segments of visitors behave compared to each other although the individual numbers might not be fully accurate. Here is an example:   new-vs-returning-visitors   Here is what we can see:
  • 78% of the sessions come from new visitors.
  • 71% of the revenue comes from returning visitors (!)
  • E-commerce conversion rate of returning visitors is six times higher than the CR of new visitors.
Of course you want to take decisions on numbers that you can trust, but such a big deviation doesn’t come for a steady rise of the new visitor percentage in the last few years. Questions to ask here:
  • Who are these new visitors and why do they convert so badly?
  • What can we do to increase the percentage of new visitors to convert?
  • Which channels drive the most new and returning visitors (dig deeper again!)?
  • Can we use smart discounts or other options to convert more first time visitors?
The 1,5 to 2% conversion rate is what we see very often. 98% of the people that visit your site don’t convert. But what if we could increase the new visitor CR and keep the returning visitor CR the same?   overall-conversion-rate BAM! Getting 2% of your news visitors convert, leads to an increase from 1,66% to 2,62% on the overall conversion rate. So it’s very worthwhile to pay attention to these ratios and to try to improve them. Some last thoughts here:
  • Don’t pay attention to the exact numbers and ratios, but spot trends, differences and insights will be uncovered.
  • Don’t overlook micro goals in this context.
  • Email signups are great in every industry so do your best to convert as many first time visitors to a subscriber during their first visit.
  • Keep on testing to increase the conversion rates of your business.
By now you should realize that there is so much wealth to be uncovered via segmentation in Google Analytics. The beauty of this feature is that you cannot ruin your data collection process. You will see the default data view again once you deselect your segments. No risk at all here! Well, I hope you have picked up a few new ideas here. Don’t forget to comment and share it with your audience if you think they can benefit from this post as well!

About Paul Koks

Paul KoksPaul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

How to Build An Insightful PPC Report in 5 Simple Steps

PPC REPORTS· 4-MINUTE READ · By Misty Faucheux on November 9 2016.   Your PPC reports display the effectiveness of your campaigns to internal and external clients, and stakeholders. Yet, most marketers still don’t know what they should include in their reports, fearing providing either too much or too little information. So, what elements make up a good PPC report?  

Always Starting With Campaign Objectives

  Your PPC report starts and ends with your clients’ goals and needs. For example, if a university is looking to increase admissions, then they will want to have enrollment leads included in the numbers. Yet, a company that is looking to increase their brand awareness may only be interested in impressions and reach numbers.   Understanding your stakeholders’ key objectives is the starting point to building your report. Yet, you also need more than raw impressions or conversions numbers. You also must put context around what they’re seeing. Many PPC reports incorporate seemingly endless spreadsheet tabs. While these may be of interest to you, the client may not fully understand them.  

Adding Context to Your Data

Your stakeholders and clients typically have their own stakeholders to which they need to justify their PPC spendings. Random numbers aren’t going to do the job. They need a story that breaks down information like the following:  
  • Current stats and how those stats compare to previous months or years
  • Where key metrics currently stand (i.e. better or worse than previous periods)
  • Causes of the increase or decrease
  • What does this mean for the business (i.e. will it have an effect on year-end goals)
  • What are you doing to improve the next reporting period’s numbers and what can the client expect
  • How does this affect long-term goals
24-month-trends   To fully create your story, you need to understand the data from which you’re retrieving your stats. Oftentimes, marketers will run reports and hand them over without ever fully comprehending what the data means. The summary is extremely important, but to create it, you must have actually completed a deep dive into your data.   Before ever building your report, make sure that you understand what your numbers are saying and how it relates to key goals and objectives.  

Selecting A Suitable Time Frame

Most marketers must submit reports on usually a weekly, biweekly, monthly or quarterly time frame. You should figure out what reporting periods make the most sense to your stakeholders and overall campaigns.   Oftentimes, weekly or biweekly reports are only high-level since they provide a snapshot of how campaigns are performing on a week-to-week basis. In this case, you might only need high-level numbers like clicks, CTR, CPC, conversions, impressions, etc. These provide a “gut-check” to your stakeholders and clients. You should, however, still have a summary of how campaigns are performing this week versus previous week(s).   ctr-clicks-stats   Reports that incorporate larger time frames (monthly, quarterly or yearly) must have more in-depth data since you’re reporting success over time. Usually, these reports include:
  • Month-over-month success data (decrease/increase in conversions, CPA, CPC, etc.)
  • What was done in the month/quarter/year to improve campaign success
  • What worked/didn’t work
  • Monthly trends that affected overall success
  • As well as everything else that goes into building a successful report (see next section)
  You may also be required to report on campaign start-to-end statistics. Known as a wrap-up report, these are required at the completion of a campaign. A wrap-up report typically includes:
  • Overall campaign successes/failures
  • Overall metrics
  • Best-performing ads/keywords
  • Learnings that can be used for future campaigns

Building The Main Structure

Whether your clients say it explicitly or not, they are interested in knowing how many sign-ups, sales, downloads and other conversions you are garnering for them – and how much it’s costing them. A comprehensive PPC report includes the following:
  • Conversions
  • Cost per acquisition (CPA) or cost per conversion (Are you reaching your target cost per conversion or CPA, or are you spending too much? What can you do to reduce it?)
  • Overall clicks/impressions
  • Ad/keyword performance
  • Device performance (especially if your company is running campaigns on multiple devices)
  • Individual campaign/network performance (Bing vs Google, Display vs. Search, etc.)
  • Campaign improvements/declines
  • Campaigns causing concern and what you’re doing to improve them OR what needs to be done to improve them
campaigns-improving These items are a starting point. Some clients may require specialty data based on their preferences or demands of their higher ups. For example, sometimes the following are requested:
  • Display placement reports and key/successful placements
  • Search queries
  • Negative keyword report
  • Time of day reports
  • Change history reports
  Work with your stakeholders to ensure that you are capturing all necessary information. You don’t want to be caught off-guard during the first meeting.  

Adding A Touch of Creativity

Typically, no one wants to look at straight numbers, and oftentimes, stakeholders need graphs and charts to add to their own reports. Create line graphs that demonstrate – for example – growth in sales or users.   growth-in-users   Or, break down month-over-month conversion and CPA performance.   conversion-cpa-performance   Whatever graphs you use, ensure that they add something to the report and aren’t simply “pretty pictures”. Most reports are way too long as it is. Only incorporate relevant data into graphs. Also, don’t eliminate raw data and substitute that with graphs. Many stakeholders will still want to dig into the raw data.  

Automating Reporting Process

Automating reports saves time and headaches. For agencies, it also reduces how many hours per month that you devote to reporting, allowing you to allocate budget to more high-priority needs. While you can create automated reports in AdWords and similar free tools, they may not fulfill all the requirements that we mentioned previously. You can use them as a starting point to pull certain data, i.e. keywords or placements.   However, if you are looking for something that can be used immediately, Supermetrics provides dozens of beautiful reporting templates for AdWords, Bing Ads, Facebook Ads and other social media channels. Best of all, they are all free and built upon Google Sheets, which offers far more flexibility and power than any dashboard tools, with pivot table, functions, charting, easy sharing and revision history.  


Before ever adding data to a report – or creating a template – remember that you must understand your client’s or stakeholder’s overall goals and objectives. If not, your data won’t meet their demands. You also need to correlate ROI and overall success metrics in your reports.   Once you understand that, build – or buy – a reporting template that meets your requirements and allows you to automate the process in the future. Always review your data (including pivot and function data results) before presenting it, and investigate any data points that don’t make sense. You need to fully understand what’s in the report if you’re going to truly articulate campaign success and guarantee stakeholder/client comprehension.  

About Misty Faucheux

20140725_0031Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

Must-Have Metrics for Every PPC Report: Looking Beyond CPC & CTR

PPC METRICS· 4-MINUTE READ ·  By Misty Faucheux on October 31 2016.     PPC metrics demonstrate the effectiveness of your campaigns. The wrong metrics, however, could be sending the wrong message to your stakeholders and clients. You need to showcase the right stats to illustrate how well your PPC campaigns are actually performing. Yet, many of us usually default to CPC and CTR without a second thought. There are, however, better metrics that could provide better campaign insights. In this article, we break down the fair, good, best – and the caveats – metrics.  

What’s Wrong with CPC & CTR?

To be honest, there is nothing wrong with tracking CPC and CTR. They tell how much traffic your ads are garnering, determine message effectiveness and how much you’re spending. CPC, for instance, tells you whether you’re wasting too much budget on clicks. For example, let’s say your clicks cost on average $10-$12, but your budget is $20 per day. You’re only garnering 1-2 clicks per day. That’s not good! You’d do better to go after less expensive, niche keywords. To change the bids for an entire ad group,
  1. Click on the Campaigns tab, and then the name of the campaign that you want to change.
  2. Click on the ad group, and then Edit.
  3. Change the default bid amount for all the keywords.
If you have a higher budget, then you can always raise your default bids if many of your keywords are below the first page bid. Another useful stat in this category is impression share. It shows how many impressions you were eligible to receive versus those that you actually did receive – and how well you’re stacking up against your competitors. There are several types of impression share metrics available, including Search Lost IS and Display Lost IS. These metrics provide info on how many impressions you lost due to limited budget or poor Ad Rank. Use these to adjust bids or work on Ad Rank. Access Impression Share by:
  1. Going to the Campaigns tab, and then clicking the Columns button (located above the stats table).
  2. Selecting Modify columns from the drop-down menu.
  3. Selecting Competitive metrics and the Impression share metrics you want to track.
  4. Hitting Save.

Tracking Conversions Is “Good”

Conversion tracking is an amazing metric. You know immediately whether your clicks are converting – or if you’re simply driving bounce rate up. Many people want to know what a conversion is: It’s really whatever you define it as. Be sure to outline this during the strategy phase. Examples:
  • Form fill-out
  • Newsletter signup
  • Webinar attendance
  • Actual sale
  • Whitepaper download
  • Engagement on-site, etc.
ALWAYS set up conversion tracking. It’s quick and painless – and necessary to determine whether your messaging and landing pages are working.
  1. Sign into your AdWords account, and click on Tools.
  2. Go to Conversions and + Conversion.
  3. Select the source of the conversions, i.e. website, app, phone call or import from offline.
  4. Create a Conversion name (one that you’ll remember).
  5. Add your metrics
    1. Value: Worth of each conversion
    2. Count: Typically, this is every conversion, but tweak as necessaryphoto2
    3. Conversion window: I’d leave this as the standard 30-day window.
    4. Category: Purchase/sale, sign-up, lead or view of a key page.
    5. Include in “Conversion”: Yes
    6. Attribution Model: Default Last Click. You can change this.
  6. Click Save -> Continue.

Why You Should Pay Attention to Bounce Rate

We mentioned bounce rate at the start of the previous section. Bounce rate refers to the percentage of people who navigate away from your site after only viewing a single page. So, why is bounce rate important? Bounce rate is like the canary in the coal mine: It can bring your attention to issues within your campaign. An extremely high bounce rate could alert you to problems like:
  • Disconnect between ad messaging and website/landing page. Don’t even think about bait-and-switch.
  • Driving people to a home page. They aren’t design to convert.
  • You’re CTA is lost in the mix. Don’t make your visitors search for it.
  • You’re not using a landing page.
Monitor bounce rate from both AdWords and Analytics if they’re connected (or using Supermetrics). PPC tends to increase bounce rate, but you should shoot for a bounce rate of 70% or lower. A 50% percent or below bounce rate would get you a gold star.  

Actual Sales/Leads Are the “Best”

For most companies, sales are the actual objective. They want to see real return-on-investment (ROI). Conversions should be compared to actual revenue numbers. The best numbers to display are:
  • Conversion rate: How often an ad click leads to a conversion
  • Cost-per-acquisition (CPA): How much your conversions cost
  • Sales revenue: Revenue can be broken up by individual or total sales
These numbers tell you exactly which keywords, ads and overall campaigns are leading to sales and revenue. Use these numbers to determine whether you are spending too much on a sale or lead. For example, if you have a product that costs $12.00, you don’t want to have a $20.00 CPA. Negative ROI won’t make clients and stakeholders happy.  

Tracking Calls Over Online Conversions

Many businesses, especially brick-and-mortar, only want to track phone calls. Call extensions on AdWords campaigns allow for phone calls to be tracked as conversions.
  1. Go to Ad Extensions, and View Call extensions.
  2. Select +Extension.
  3. Select the campaign, and Done.
  4. Select + New phone number.
  5. Add the number, and then Save.
photo4   Google also allows you to use forwarding numbers in ads.  These numbers capture information like call duration, start/end time and area code. If you set up call tracking in the Conversions column, you can track it there. If not, go to Ad Extensions to view call conversions.  

Tying it All Together

These are only a few examples of the types of advanced PPC analytics available to you. Experiment with different metrics and reporting until you find the right mix that best tells your side of the story. All of your metrics can work together to create a cohesive picture of campaign successes. The more that you can prove the value of PPC, the more likely your clients and stakeholders will continue to fund your efforts.  

About Misty Faucheux

20140725_0031Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.

How iProspect Leverages Supermetrics Solutions for its Clients’ Benefits

SUPERMETRICS USER CASE· 3-MINUTE READ ·  By Axel Queffeulou on October 24 2016.

As a leader in digital marketing, iProspect has a large and diversified client portfolio. When faced with such a large number of clients and projects, agencies must constantly find new ways to make their processes more efficient, regardless of the type of work they are confronted with.

When it comes to dashboards and report creation, many time management and organization issues can emerge. In fact, time could be spent needlessly on reports, time where many errors could be made.

To solve these problems, iProspect analysts are happy to use Supermetrics, which we have found to be the right tool for this issue. Indeed, in just a few seconds it allows us to grab all the data needed from various APIs. With just a few clicks, informative and stylish dashboards as well as complex reports can be updated.

Additionally, the flexibility of the software is incomparable. There is a choice between an Excel or a Google Drive Spreadsheet version. Although both versions are quite similar, Supermetrics allows you to leverage the benefits and power of each platform. The choice will simply depend on your needs.

For example, what if the iProspect Paid Search Team Leads want to follow the performance of their campaigns running on several platforms (Adwords, Bing, Facebook Ads) on a daily basis with a quick snapshot? In a single worksheet that can be automatically updated on the Google Drive version, the managers get a clear and comprehensive overview of what’s happening without having to jump across different platforms for all campaigns that are being managed by analysts within their team.

Furthermore, Supermetrics provides a great way to avoid data sampling in Google Analytics by partitioning the data. Oftentimes sampling can significantly impact the data and consequently skew the reports. For companies that cannot afford to have a Premium Google Analytics account, this feature gives Supermetrics a strong competitive advantage


These benefits, and many others, make Supermetrics a top choice for iProspect when it comes to dashboards and reporting automation.

 6-2-2015 9-47-47 AM.png

iProspect Use Cases


Overspend Control Dashboard

iProspect uses Supermetrics for Google Drive to get the daily cost data for Twitter Ads, Facebook Ads, Adwords and Bing Ads and compare the sum to our budget. An automatic email-triggering system alerts the managers by email as soon as spend goes over budget (which is very rare, by the way!)



Budget Pacing for a specific Paid Media account

Our Paid Media specialist uses Supermetrics to plan their budget spend overtime and keep on eye across the account they manage.


Data Collector for a third-party

One of the great thing of Supermetrics is the ability to query multiple accounts (let’s say Adwords account) in one single query. Other tools in the industry would only have API connectors to access a single account. iProspect uses Supermetrics to gather data from multiple accounts at the same time and we use the collected data as an input for Data Visualization third-party systems.



Bing Ads Cost Data Upload

In Google Analytics, we all know the Adwords connection is great to have the clicks/impressions/cost data in GA. For Search Engine Marketing, Adwords is just one part of the picture. With Supermetrics, we use the Bing Ads Cost Data Uploader to fill the gap and get the data from Bing Ads to GA!



Since we’ve started to use Supermetrics a few years ago, we’ve been adding more and more licenses to our account.  Some of our internal development projects were abandoned because Supermetrics would deliver more solid solutions at a cheaper rate.

In a data-driven environment we’re building today (Internet of things, Big Data, BI… you name it), at iProspect we do think it’s important to know how to use smart and agile solutions like Supermetrics . We do it on a day-to-day basis to get quick automation wins and get on with other projects.


About Axel Queffeulou

Axel-Queffeulou-460An engineer, Axel has been using his technical skills for the past five years at some of Montreal’s largest agencies. He is now able to develop his managerial side as well after being given the opportunity to build a Data & Analytics team at iProspect. In addition to developing new client-related services, Axel offers his knowledge and support in data and reporting to the Paid and Earned Media departments. Beyond client service, to fill his obsession with analytics, Axel enriches the world by giving back and teaching Digital Analytics at conferences, university classes and trainings. Similarly, Axel wants to see analytics properly used dispersed in all industries.      

4 Brilliant TED Talks That Will Make You a Better Data Analyst

DATA ANALYSIS · 6-MINUTE READ · By Oscar Santolalla on October 17 2016   Think of your favorite artist. Think of an inventor you admire. For them, new ideas are essential, like their everyday’s meal. Without new ideas, they could not create anything great.   In their process to create things, they must solve numerous problems too. The right new idea can help us to solve a difficult problem that feels like a puzzle with one piece missing. Watching TED talks is an easy—and often entertaining—way to get new ideas.   As a data analyst you are faced to a series of tasks and activities: choose the right data to analyze a problem, analyze the data, learn or perfect your data visualization skills, tell stories out of results, think critically, put data into real problems’ perspective, ease decision makers’ job, etc.   This article presents you a selection of great TED talks in which the speaker either used data analysis as the main topic or showed great examples of insight with effective data visualization in order to support her points.  

The beauty of data visualization by David McCandless

(TEDGlobal 2010)    McCandless’ talk is great for two reasons. First of all, he shared his personal journey on how he became an expert in information design and data visualization without ever having enrolled to a design school. He learned through doing.   Secondly, he delights us with amazing data visualizations that make non-obvious conclusions easier to understand. For instance, every single day the media reports some billion-dollar amounts. Without context those numbers don’t make sense. McCandless created the $Billion Dollar o-Gram which allows to visually and relatively understand the amounts (e.g. OPEC’s revenue 780 billion a year vs. their 3 billion climate change fund) as well as their motivations and correlations.   700_billion-dollar-2013   McCandless in his own words “I wanted to say that it feels to me that design is about solving problems and providing elegant solutions, and information design is about solving information problems.” Unlike experts that say “data is the new oil”, McCandless believes that data is the new soil. And this is because for him, data feels like a fertile, creative medium. And visualizations are flowers blooming from this soil.   Main Takeaways:
  1. Treat your data as a soil. Complex data can be turned into beautiful and easy to digest visualizations to ultimately solve people’s problems.
  2. Use design to solve problems. If you want to master information design, probably the best way is to read “Information is Beautiful” or other McCandless’ books.

Making data mean more through storytelling by Ben Wellington: 

(TEDxBroadway, February 2015)         This is one of my favorite talks in this list. In this funny and very actionable talk, Wellington shows us his nifty guide to better data storytelling. He defines himself a Data Storyteller. And I think you should become a data storyteller too. As a rock star data analyst, storytelling can make your fantastic work win people’s hearts and minds. Wellington’s own story started with the blog “I Quant NY” in which he started to use publicly available data of New York City and make experiments. He combined data science with urban planning, such as mapping the city per bicycle accidents’ zones.   267c47038a922c3e88fd39edfcb37530 Wellington’s A-ha moment occurred when he noticed that it was his “improv comedy” background what helped him to make his writing a success. He was much more compelling than a typical data science blogger.     Main Takeaways:
  1. Anybody can be a data storyteller.
  2. Data storytelling in five steps is:
    1. Connect with people’s experiences
    2. Focus in one idea  
    3. Keep it simple
    4. Explore the things you know the best
    5. Make an impact

How to use data to make a hit TV show by Sebastian Wernicke

(TEDxCambridge, June 2015)    Wernicke starts with a fascinating story of Amazon and Netflix, how highly specialized teams inside these two companies use tremendous amount of user data. These teams’ goal is to select a TV series that will be produced and featured. This TV series must become the next big hit. The very different results obtained by these companies helped us to illustrate a pattern for data-driven decision making. The winning team—the one in Netflix—analyzed a huge amount of data but didn’t allow the data to make the final decision. They took their own risks and decided to produce “House of Cards” (U.S. version).              blog-post2   The pattern for data-driven decision making has two parts. The first one is, taking a problem apart into its bits and pieces for deep analysis. Data is great for this first step. The second is putting all of these bits and pieces back together again to come to your conclusion. Human brain beats data in this step. In this very entertaining talk, Wernickes compares bad decision making with using the fortune-telling toy called Magic 8 Ball. What is that? You have another reason to watch the talk.     Main Takeaways: When you have a complex problem to solve with data analysis:
    1. Take the problem into pieces, using data and software. Analyze deeply.
    2. Put the pieces together. But don’t let data make the decisions for you. In this second step, an expert’s brain taking risks performs better than just data. It’s not data but taking risks what will make you achieve extraordinary results.

Why smart statistics are the key to fighting crime by Anne Milgram

 (TED@BCG San Francisco, October 2013)  It’s fascinating to see an attorney speaking with such a passion about data and analytics. In 2007, Anne Milgram became the Attorney General of the State of New Jersey, US. In the most dangerous city in the country, policemen were using outdated tools such as “yellow Post-it notes” to investigate suspects and fight crime. Milgram led a transformation to effective data-driven policing that considerably reduced crime. Later she moved to work on Justice. Her new challenge was to help judges to assess: if I release this suspect, what is the risk that he will commit new crimes? See “Pretrial Assessment Dashboard” which is an excellent example of using insight to give recommendations based on data.   blogpost3   Milgram believes in the equation “Data + Instinct = Better Decisions.” This is what judges in US are gradually doing today thanks to the data-driven risk tool that is being developed and deployed across the country. Data analysts can apply the same equation to solve thousands of other problems in society.                   Main Takeaways:
  1. You don’t have to be a data analyst or big data expert to make a difference with data
  2. As a data analyst, you can teach people from other professions about how data analysis can solve their own problems. Evangelize data analysis.


Design, storytelling, risk-taking and data evangelism. Four main lessons from these formidable TED talks. Are you empowered with these new ideas? Great. Let’s put these ideas into action, in your current or next project. You will become a better data analyst. You will be able to solve more difficult problems. And you can make a difference for both your business and the society. Are you ready to take one of these ideas into action today?  

About Oscar Santolalla

OscarOscar Santolalla Host and Producer of the public speaking podcast Time to Shine. Oscar has spent more than three years as a Product Manager in the software industry. Either onstage or on blogs he advocates making technical presentations and product demos that engage and inspire. He is currently writing the book Create and Deliver a Killer Product Demo.

Five Custom Filter Types Every Business Owner Should Set Up

CUSTOM FILTER · 6-MINUTE READ · By Paul Koks on October 10 2016 


Google Analytics collects data at the property level, but you have the powerful option to create separate reporting views. Most often the difference between what data is being collected in each view is made through setting up a set of filters.


Segmentation is what makes your Google Analyics data reliable and actionable. There are different techniques to segment your data. You could use (advanced) segments, secondary dimensions, custom dimensions, but also filters. In this post I will describe five different filters you should consider setting up. Let me first explain a bit more about filters.


Google Analytics Filters

Setting up filters requires you to have “edit” rights on the account level. This is because filters are stored on the account level and are applied at the reporting view level.


Filters in admin section


This might cause problems if you work as a consultant and the company you are employed at has multiple properties installed in their account. Sometimes they don’t want to give you access to all their web properties. So make sure to sort this out at the start! Keep in mind:

  • Filters permanently affect the data being collected in the reporting view.
  • Filters can only be used on the dimension level; so you can’t set up filters on a metric.
  • Filter order might matter if you apply multiple filters to one view.
  • Apply filters to a test view first before you add them to your main data view.
  • There might be a short delay (up to a few hours) before applying a filter affects your data.


I recommend to first experiment with applying segments in your reporting environment before you start working with filters. Segments temporarily affect your data and are in that way harmless. Once you understand how they work you can move on to filters.


1. IP Address Filters

In order to collect accurate data, you don’t want your internal sessions to show up. I recommend to use filters on IP address to filter out as many “known” sessions as you can. These sessions don’t reflect usual client or prospect behavior.


Normal IP Address

Filtering out single IP addresses is easy. Just head over to an IP address checker and copy the address from the screen. The next thing you need to do is set up the filter in Google Analytics and apply it to the main view:


Exclude sessions Paul


Be careful to select “exclude” instead of “include” when setting up this filter. If preferred, you can use a predefined filter as well:


Exclude sessions Paul (2)


You are allowed to set up multiple exclude filters of the same type so there is no need to add all IP addresses to one exclude filter.


IP Address Range

A lot of companies have a range of external IP addresses in use. If this is the case, you need to use a regular expression when you set up this filter. Here is an example:

  • First IP:
  • Last IP:


The IP Range Regular Expression Builder comes in handy now:


IP Address Range


Now you can create a RegEx filter in Google Analytics:


Exclude sessions office range


In this case you can only use a “custom” filter. A predefined filter won’t do as you can only select “that are equal to”, “that begin with”, “that end with” or “that contains”. To conclude, custom filters handle the more advanced stuff if compared to predefined filters. In my opinion, once you know how to use regular expressions, it might be wise to just use the “custom” filter option!


2. Lowercase Filters

The second type of filters are the so-called lowercase filters. I use these filters as an extra safety net for getting the naming structure right. At a minimum make sure to set up a lowercase filter on:

  • All campaign tracking parameters (utm parameters)
  • Search term (internal site search)
  • Hostname


Let’s take a look at an example below:


Lowercase Campaign Medium


Getting campaign tracking right is crucial. These filters are really useful to correct certain mistakes. For example:

  • Alex uses Email to define Email Campaigns
  • Mick uses email to define Email Campaigns


On default, Google Analytics will register both “Email” and “email” as a medium. However, setting up this filter will force all characters of campaign medium to be lowercase. Very useful since all sessions will now registered under “email”! I recommend to set up a lowercase filter on all different utm parameters (five in total). In addition to that you want to have your internal site search terms to be in lowercase as well. Capital characters don’t have any meaning in the site search reports. The same counts for hostname; make sure Google Analytics registers only lowercase characters here!


3. Device Filters

In-depth cross-device analysis and optimization can only be done if you can follow your visitors across multiple devices. In reality this is often not the case as we can’t easily apply the user ID feature in most cases. Using device level filters is great if you want to analyze your devices separately and are tired of sampling. It is very easy to set up. Just head over to the filter section and fill in the details shown below:


Include Mobile


This filter – if applied at a specific view – allows you to isolate mobile traffic. All the reports you will see are fully focused on mobile. You don’t have to use any segments and it’s possible to view your goal funnels for mobile as well! Non-premium funnels cannot be segmented in another way. Keep in mind that you do want to have a reporting view where all device types are measured. Sometimes you simply want to quickly compare the different devices types or have multiple device segments applied within the same data environment.


4. Traffic Channel Filters

There might be several reasons why you want to set up traffic channel filters. For example, you have hired an SEO agency and want them only to have access to the SEO numbers. Or you don’t want another party to have access to your Google AdWords numbers. In both cases filters are your best friend! In the first example you want a certain company to only have access to your SEO numbers. SEO traffic is measured under medium = organic. The following filter will help you out:


Include only organic


The reporting view where this filter is applied will only collect organic/SEO data from this point on. Make sure to immediately apply this filter after you set up the separate view if you don’t want any other traffic to appear in this view. Please note that you are not able to set up filters on (default) channel groupings. You should use segments if you want to segment on a specific channel group. Channel groupings are especially useful if you have messed up your campaign medium/source structure in Google Analytics. In addition they more accurately measure your social traffic.


5. Search and Replace Filters

I won’t give any specific guideline here, because the way you use them depends on your unique situation. Search and replace filters can help you to:

  • Replace URLs with difficult to read product IDs in product name based URLs.
  • Quickly correct incorrect media name types.
  • Prevent duplicate content URLs from showing up in Google Analytics by removing technical parameters.


I am just touching the surface of what’s possible with these type of filters. Let’s assume you run a campaign and a third party agency made the following mistake:

  • Utm_campaign = witer 2016 instead of winter 2016.
  • They are not able to replace this value and the campaign runs for another two months.


You want to keep your data as clean as possible. So if you notice this issue soon enough, you can correct future sessions from this campaign by using this filter:


Replace witer by winter


It’s as easy as that! There are many more ways to use filters in a smart way. These examples will unleashen your creativity to create and apply filters that match your unique situation best. I cannot stress enough that you should:

  • Keep a raw reporting view (with no filters applied).
  • Have a testing view (where you apply your filters first).
  • Use the “verify” filter option whenever possible; it will help you prevent making mistakes in the first place.


How to Get it Right

A few more concluding thoughts:

  • Plan out your account structure (with properties and reporting views) first.
  • Think about which filters you need in each of your reporting views.
  • Add all filters to your account.
  • Test your filters first if you are unsure or relatively new to using filters.
  • Check each of your reporting views and add the filters that you need.
  • Make sure your filter order is set up correctly. One filter can influence the outcome of the other.
  • Watch the data flowing in (real-time reporting, debugging tools) and correct the setup if needed.


Well, this is it from my side. I hope you have learned some cool, new stuff about Google Analytics filters! I am happy to hear your thoughts! What are your favorite filters and how do you use them?


About Paul Koks

Paul KoksPaul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

How to Explain Data Discrepancies Between Facebook and Google Analytics

FACEBOOK  & GOOGLE ANALYTICS · 10-MINUTE READ · By  Kayla Eide-Hall on October 3 2016


Are you struggling to reconcile Facebook analytics data with third-party data from Google Analytics? Not sure how to present both sets of data to your client? Wondering how to explain the discrepancies?


You’re in luck. Whether you’re trying to evaluate paid Facebook ads, or you want deeper information about an organic Facebook campaign, this guide is for you.


The first five sections address the five major stats used to track Facebook initiatives. Each section explains how data differs in Facebook compared to Google Analytics, and how to take advantage of both.


The section explains how to create a report that integrates Facebook data and Google Analytics data, so you can take advantage of all data when presenting results to your client.


Stat to Track 1: Paid Facebook Conversions


When it comes to conversion tracking for Facebook ads, boosted posts, and other paid advertising methods on Facebook, make sure you’re comparing apples to apples. Because Facebook’s Ad Manager/Pixel and Google Analytics use two different tracking methods to gather performance data, you have to be aware of these differences and adjust settings so that both sets of data are as similar as possible.


Unlike Google Analytics, Facebook tracks indirect “non-linear” conversions, meaning that if a user clicks your Facebook ad and views your site, leaves your site, then returns the next day and makes a purchase, Facebook attributes that conversion to Facebook. Google does not. Google Analytics tracks only direct last-click conversions — when a user clicks your Facebook ad, views your site, and converts right then and there without leaving.


You also need to know that Facebook’s default attribution model is different from Google’s. According to Facebook’s official help page on the subject, Facebook conversion reports use a default 28-day window for click-through conversions and a one-day (24-hour) window for view-through conversions. By uniquely tracking view-through conversions, Facebook takes credit for a conversion even if a Facebook user only sees your Facebook ad without clicking it, then visits your website and makes a purchase. Furthermore, Facebook doesn’t differentiate between the two types of conversions; click-throughs and view-throughs are combined into a single data point for total conversions.


View-through conversion tracking is something Google can’t do for Facebook traffic to your site. In contrast, Google Analytics records this conversion type as a direct source conversion. As far as Google is concerned, that same user typed your web address into their browser without influence from another online source. (Tracking parameters like UTM codes can’t help you here.) Google has no idea the user saw your Facebook ad.


Finally, Facebook tracks cross-device conversions (mobile to desktop, desktop to tablet, and so on) better than Google does. This is because whereas Google installs a single-location cookie to track a user’s activity on a single device, Facebook tracks activity using its Facebook user profiles (and the on-site Facebook Pixel). Facebook’s reference point for tracking a single user is more easily transferrable across devices.


The result is that when a Facebook user clicks your Facebook ad on their smartphone and visits your site without purchasing, then later returns by typing the web address into their browser on a desktop PC while logged into Facebook, Facebook reports that purchase as a Facebook conversion. Google reports it as a direct source conversion. Again, Google has no idea that Facebook was involved in the conversion.




1. Be aware that Facebook’s view-through conversion tracking may not be accurate. Just because Facebook showed a user your ad doesn’t mean the user actually saw the ad before visiting your site. Perhaps the user already knew of your site and coincidentally visited it without influence, then made a purchase. Either way though, Facebook takes credit for this assumed view-through conversion.


2. Remove 24-hour view-through conversions from your Facebook attribution settings. Do this if you want to simplify conversion tracking, and you don’t mind excluding view-through conversions from your data (recommended). After removing view-throughs, your total click-through conversion numbers should match up better between Facebook and Google Analytics.


To remove them, log into your Facebook Ads Manager account, then click the Columns drop-down menu and select Customize Columns.




Next, click Change Attribution Window in the bottom right-hand corner of the pop-up window.


C:\Users\Kayla\Desktop\Facebook images\Img2-customize-columns.PNG


Now, check the box for your preferred click-through attribution window setting under “After Clicking Ad”. Then, exit out of this small window by clicking outside of it, and click Apply. By only selecting a click-through setting and not selecting a view-through setting (under “After Viewing Ad”), you effectively turn off view-through conversion tracking. Facebook will now only track click-through conversions, like Google Analytics.


C:\Users\Kayla\Desktop\Facebook images\Img3-attribution-settings.PNG



3. Review Google Analytics-reported Top Conversion Paths under the “Multi-Channel Funnels” report. As Google’s multi-click conversion report, this report can help you either confirm or debunk whether your Facebook campaigns are contributing to conversions as much as Facebook data wants you to think they are. (Advanced Google Analytics users can also use this report to guide their creation of a custom attribution model for increased control over conversion tracking.)


C:\Users\Kayla\Desktop\Facebook images\Img4-top-conv-paths-report.PNG



4. Pay attention to direct source conversions in Google Analytics when you’re running a Facebook campaign and include this metric in your reports. Remember (and remind your client) that this data may include conversions Facebook is taking credit for due to non-linear tracking and/or due to cross-device activity.


Facebook almost always reports a higher number of conversions than Google Analytics. Its tracking methodology is set up to make Facebook appear as valuable as possible. To account for this, you should take Facebook data seriously, but also with a grain of salt, and compare it with Google’s data for the most accurate big picture.



Stat to Track 2: Unpaid Organic Facebook Conversions


Tracking website conversions for unpaid “organic” Facebook referrals (such as clicks on a non-boosted Facebook post) requires a different strategy from tracking paid ad conversions, because this type of conversion isn’t tracked in Ads Manager or Facebook Insights. In fact, the only way to track these organic conversions is to use Google Analytics or another third-party analytics software.


Fortunately, Google Analytics can show you Facebook referral traffic with conversion data for individual landing pages/URLs. Simply navigate to Acquisition>Social>Conversions, and select Facebook under your listed Social Networks. (If no Facebook conversions have been recorded for the selected date range, Facebook will not appear in the list).


C:\Users\Kayla\Desktop\Facebook images\Img5-ga-social-conversions.PNG


However, if your Facebook page and/or multiple Facebook posts include several links to the same landing page, then tracking only landing page performance for Facebook referrals won’t show you the big picture. You’ll see what landing pages are working, but you won’t see which posts or Facebook page links are working.



To get more detailed data in Google Analytics on conversions for individual Facebook links, create a custom URL for each of your unpaid Facebook posts/page using UTM parameters. Google’s URL builder makes it easy to create these custom URLs every time you need a new one.


Make sure to enter “facebook” as the Campaign Source tag to record traffic from this URL as Facebook traffic. Also enter a unique identifier for the specific promotion you’re running as the Campaign Content tag, again to record traffic accordingly.


C:\Users\Kayla\Desktop\Facebook images\Img6-google-url-builder.png


Now you will be able to see conversion data for individual Facebook posts/links, because you’re giving each its own custom URL to be tracked.



Stat to Track 3: Facebook Clicks vs. Google Sessions


One exceptionally common complaint that marketers have when comparing Facebook Insights or Ads Manager data to their Google Analytics data is that the number of click-throughs to your website reported by Facebook doesn’t match the number of Facebook-referred sessions reported by Google.


Both Facebook Insights and Facebook Ads Manager show you how many people clicked an ad, post, or page link. Google Analytics similarly shows you how many people were referred to your site by Facebook in the form of sessions, and allows you to drill down by landing page. However, clicks are not the same as sessions.


There are three main reasons you will likely see discrepancies between Facebook click data and Google Analytics sessions data:

  • If a user clicks your Facebook post more than once in 30 minutes, Google Analytics records only a single session. In this case, two Facebook clicks equal one session.

  • If a user clicks your Facebook post and visits your website, then becomes inactive for more than 30 minutes (times out), and then re-engages with your site after 30 minutes, Google will record two separate sessions. Still, Facebook reports only the single click. In this case, one Facebook click equals two sessions.

  • When a user accidentally clicks your Facebook post and immediately clicks out of the still-loading landing page, Google Analytics may not have time to record a session.




First, make sure your website records as many sessions as possible by ensuring that your Google Analytics tracking code is placed as close to the top of your site code as possible.


Also, include both the click and session metrics in your reports to get a more accurate understanding of how users are engaging with your site after clicking through from Facebook. By comparing Facebook-reported clicks with Google-reported Facebook referral sessions, you can assess whether or not those clicks you see in Facebook are truly valuable.


Go even further by checking your average session duration and pages per session metrics in Google Analytics (under Acquisition>Social>Network Referrals>Facebook). Are users spending time on your site once they arrive from Facebook, or are they leaving immediately? Do they stay on the first landing page, or do they continue on to explore additional pages?


Stat to Track 4: Facebook Demographics vs. Website Demographics


Are you targeting the right market with your Facebook campaigns? Find out by analyzing demographics data across both Facebook Insights and Google Analytics.


Facebook Insights provides valuable demographic information about the people who engage with your Facebook page. Similarly, Google Analytics provides demographic information about your website visitors.




Learn more about the Facebook users who engage with your website. While all interaction with your Facebook page is valuable, the users who continue on to interact with your site are presumably more valuable than those who don’t.


To investigate, navigate to the “Your Fans” report in Facebook Insights under the “People” section. Record the available demographic data, including the gender percentages (Men vs. Women), age range percentages for each gender, number of fans by country, number of fans by city, and number of fans by language spoken. Record this same data for “People Reached”.


C:\Users\Kayla\Desktop\Facebook images\Img7-fb-insights-people.PNG


Now, go into Google Analytics and obtain the same data for Facebook referral sessions in the last 28 days (which is the default date range for Facebook Insights). To do this, navigate to Audience>Demographics>Overview.


C:\Users\Kayla\Desktop\Facebook images\Img8-ga-demographics-menu.png


Here, create a custom segment. Click Add Segment, then click +New Segment and select Traffic Source from the left-side menu. In the Source field, enter “facebook” and make sure “contains” is selected in the drop-down menu. To finish, enter a name for your segment and click Save. This custom segment will now show you gender and age data for your Facebook referrals.




This same segmentation method can be used to find location and language data in Google Analytics, reported under the Geo tab (below the Demographics tab).


Compare the two sets of data (Facebook Insights vs. Google Analytics) to gain insights into how Facebook is driving engagement with your brand. Perhaps you have a large number of Facebook fans in one age range, but the Facebook users who actually click through to your website are from a different age range.


Once you discover differences such as this, you may be able to adjust your Facebook strategy accordingly. Is your Facebook content geared too much toward the wrong age range? Are you failing to engage one gender compared to the other? Test new ideas and watch how your data changes (or how it doesn’t).



Stat to Track 5: Facebook Engagement vs. Website Engagement


Knowing what works on Facebook is good. Knowing what works on your website is also good. Thinking about them together is even better.


Facebook Insights gives you a lot of information that Google can’t about what’s working on Facebook. Conversely, Google Analytics gives you information that Facebook can’t about what’s working on your website.


Unique Facebook Data:


  • Page Views

  • View Sources

  • Actions On Page

  • Post Reach

  • Post Likes/Reactions, Comments, Shares

  • Positive/Negative Feedback

  • Spam Reports

  • New Likes/Unlikes

  • Organic vs. Paid Likes

  • People Nearby


Unique Google Analytics Data:


  • Time On Site

  • Bounce Rate

  • Avg. Session Duration

  • Pages Per Session

  • Second Page Viewed




Similar to the way you can compare demographics data from Facebook Insights and Google Analytics (see Stat to Track 4), you can also benefit by comparing data on user behavior.


For example, using the Google Analytics Social Network Referrals report (shown below), you might look into which page on your site visitors navigate to (Second Page) after clicking through from Facebook and arriving at the first landing page. Perhaps you’ll find that a particular landing page often leads users to perform a search using your site’s search function. Upon discovering this pattern, you may realize a different landing page would be more effective to include in your Facebook post/page.


C:\Users\Kayla\Desktop\Facebook images\Img11-ga-network-referrals.png



Creating an Integrated Report with Facebook & Google Analytics Data


Combining data from Facebook and Google Analytics into one integrated Facebook report (either manually or through report automation) is a surefire way to cover all of your bases when making strategy decisions, and to prove to your client that your work is producing results.


To create your integrated report, follow these four simple tips:


  1. Choose the right KPIs/metrics to report based on your client’s goals, and organize them together accordingly. For an in-depth guide on how to do this, check out the article “How to Present AdWords Results for Happier Clients,” which provides tips that can be applied to Facebook reporting just as they apply to AdWords reporting.


  1. For duplicate metrics (for example, total conversions reported by Facebook and total conversions reported by Google Analytics), report the two metrics side by side, clearly identified as Facebook data and Google data. Follow up those two metrics with their average value, as illustrated below.



  1. Include notes on the differences between similar metrics. For example, note which type of Facebook conversions you’re reporting (view-through and click-through, or only click-through) and the type of Google conversions (click-through).



  1. In addition to including notes on your metrics, add in-depth commentary on the meaning of the data. Which data points show success? Which show room for improvement? Are there certain data points that prove your work has been effective? Point them out.


Finally, when presenting your Facebook report to your client, keep at the forefront of your mind the differences between Google Analytics data and Facebook data, so you can help your client see the bigger analytics picture. With that big picture, both of you will be able to discuss more easily what’s working and what isn’t, and how to move forward based on all of the data you have at your disposal.


Happy reporting!


About Kayla Eide-Hall 

kayla-eide-hallKayla Eide-Hall is a freelance writer and editor for various publications. She has experience writing on topics that range from home technology and business IT to jet charter destinations and small business marketing. Kayla lives in San Diego and holds a degree in Journalism from San Diego State University.

How to DIY PPC Budget Pacing Report in 10 Minutes (by Lunametrics)

BUDGET PACING · 3-MINUTE READ · By Andrew Garberson on September 27 2016


Saying goodbye to expensive advertising reporting tools was easy. No more sales calls. No more closed code report limitations. Way more budget for other fun tools.


But I really missed the budget pacing calculator.


Budget pacing calculators help digital advertisers meet ad spend targets each month. Companies would not have budgets in a perfect world, but most companies don’t live in a perfect world. A portion of the annual operating budget is set aside for marketing and the SEM manager gets a slice of that for digital advertising. Divide it by 12 and the monthly ad budget is born.


AdWords and other digital ad networks that set budgets at a daily level benefit the most from pacing tools. It can be difficult to meet monthly goals with complex accounts that evolve quickly. Adding new match types, pausing poor performers, launching new campaigns, and testing ad formats all influence account direction and spend. A way to pace the budget is essential.


The good news: You’re 10 minutes from your own in Google Sheets. Supermetrics makes it easy.

Screen Shot 2016-07-21 at 3.12.25 PM.png

Several formulas are required but no serious spreadsheet wizardry. It is easy to design and I have done most of the work for you (although feel free to talk all of the credit with your boss).


Start by importing cost using Supermetrics or the Google Analytics plugin for Sheets. In Supermetrics, it might look as simple as this.


Screen Shot 2016-07-21 at 3.43.12 PM.png


Now it’s time to add some formulas to either this tab or another tab that references this one. I like to use another tab so I can adjust the rhetoric, but either will work.


Add the formulas in row 16 to 19 to begin. Don’t worry about the data in rows 20 to 24. We will get to that later.  


Screen Shot 2016-07-21 at 3.54.33 PM.png


NOTE: Don’t use the periods at the beginning of the formulas. I had to add those to expose it for you. Drop the periods on the far left.


You now need to update the red formula to match your sheet and budget. The first part, “Budget!D27,” is simply referencing the cost that we imported from AdWords. The second part, “25000,” is the monthly budget. Update that to reflect yours.


Once those changes are made, it should look like this.


Screen Shot 2016-07-21 at 3.57.18 PM.png


The next (and most rewarding) step is visualization. I used a horizontal bar chart that compares current monthly AdWords spend to current portion of the month. The chart settings and final product look like this.


Screen Shot 2016-07-21 at 4.01.19 PM.png


Finally, let’s return to the strange “Monthly Spend” data that I placed in rows 21 to 24. I like to do a second data pull from Supermetrics to catch historical spend from previous months. I add it as an additional graph in my report to show spend over the 3 prior months.



Screen Shot 2016-07-21 at 4.02.52 PM.png


You’ve done it. Just 10 minutes (or so) and you have your own budget calculator. Now go show your boss and coworkers the cool thing that you built!

P.S. I’ve just shared with you this Google Sheets, which can give you a better view of my report building process. However, if you are looking for something that can be used immediately, check out this Client Budget Tracker & Alert . It automatically calculates your clients’ budgets, notifies whether you are under-spending or over-spending and gives you more time to focus on the things that matter!



About Andrew Garberson

Andrew GarbersonAndrew Garberson is Manager of Search at LunaMetrics, a Google Analytics partner and search marketing consultancy. In addition to leading the SEO and PPC teams, Andrew is an analytics junkie with a special interest in conversion optimization. For more from Andrew, find him on Twitter, his personal site or the LunaMetrics blog.

How to Measure Conversion After The Retirement of Converted Clicks

ADWORDS’ RETIRING CONVERTED CLICKS · 8-MINUTE READ ·  By Misty Faucheux on September 23 2016 


If you’ve been in AdWords lately, you’ve seen the notification that Google is retiring Converted Clicks. In fact, it will no longer support the metric starting on September 21st. Google is forcing all marketers to use what it considers the more comprehensive metric: Conversions. The good news, however, is that most of us have been using the metric for a long time.


The Difference Between Converted Clicks and Conversions

According to Google, Converted Clicks is a click metric that counts the number of clicks that result in one or more conversions. Their example includes someone who clicks an ad once, but then goes to a website and performs two different conversions. Unlike conversion tracking, converted clicks would measure all these conversions as a single click. Conversions, on the other hand, would track the different conversions separately.

While this was helpful in determining which types of clicks or ads were performing well, it didn’t provide information on what is usually the most important data needed to track ROI: actual conversion numbers.

Other limitations of converted clicks include that you can’t:

  • Segment them since one click can lead to different conversions, but you can’t really see the data on these different conversions, i.e. conversion name, source or category.

  • Use the “Include in ‘Conversions'” setting, which allows you to exclude certain conversion actions

  • Add a conversion value

  • Measure clicks that lead to a store visit or measure across devices.

Part of the retirement reason has to do with these limitations along with the following: Google believes that Conversions are simply a better measurement tool. It allows you to track how well your ads are performing and lets you see the exact number of conversions. The main difference between the two, however, is that Converted Clicks is a click metric, and Conversions is a bid metric. Bid metrics actually provide you with a better overall picture of your campaigns and overall AdWords success.

In fact, Google itself said that converted clicks are “a limited way to measure the results from your ads because it is tied to a single click, and it doesn’t lend itself to measuring behavior that spans multiple conversion events or multiple clicks.”

Other differences between Converted Clicks and Conversions include that Conversions give you the ability to:

  • Count either “every” or “one” conversion. For example, a retail business might want to count “every” online purchase, but only count “one” conversion for a coupon download – no matter how many times a customer downloads it.

  • Measure cross-device conversions (located in the Settings sections of your Conversion actions)

  • Track the value of your conversions and exclude certain conversion actions, which are both part of the “Include in ‘Conversions'” setting.

  • Add columns to your AdWords reporting that provides you with information on Conversion Rate and Cost-per-Conversion.


Changing Your Conversion Bid Metric

Most marketers were only using Converted Clicks if they were using Target CPA or Enhanced CPC as their Bid Strategy and Converted Clicks as their Conversion bid metric.

If you are, you will need to change your Conversion Settings to “Conversions”. To do this, click on Tools -> Conversions, and then Settings.

Change the Conversion bid metric to Conversions, and click Save.

If you fail to change to Conversions before Google retires Converted Clicks, Google will send out an automated migration tool along with a reminder to accounts still using the metric.

Note: If you were using Converted Clicks, be sure to download any historical Converted Clicks data before changing over to Conversions. You will lose this data if you don’t save it before the changeover. Also, be sure to refresh your Supermetrics reports once you’ve completed the transfer.


Tracking Conversions with Conversions Metric

Tracking conversions is fairly straightforward, but you will need to know what types of conversions that you need to track. Google provides you with the ability to track Website, App and Phone Calls. You can also import data from other sources if you wish to track offline conversions.

Yet, after 15 years of using Converted Clicks, many marketers might find this latest update challenging. Now, you have to change the way that you report and analyze campaign performance using only Conversions metric. To minimize any damage from the change, Google recommends that you manually prepare to make the move from Converted Clicks to Conversions.


Change the Count on Conversions

To ensure that your reporting is correct, you must change the Count. As mentioned previously, Converted Clicks only counts one click per potentially multiple conversions. Conversions count every conversion action. For reporting, this could be the most confusing for marketers making the switch. This requires not only a mental adjustment, but also a change in settings.

To change the Count, follow these steps:

  1. Tools -> Conversions, and click on the conversion action that you want to edit.

  2. Select Edit settings.

  3. Change the Count. If you want your conversion count to be similar to the old Converted Clicks, select “One” as your conversion option. This will count up to one conversion per conversion action. For sales, however, you may want to count “Every” conversion since each of these conversions may lead to revenue.

  4. Select Include in “Conversions”. This ensures that your conversion data shows up in the Conversions reporting Column.

  5. Click Save.


It may take up to two weeks for campaigns using Target CPA or Enhanced CPC bidding strategies to adjust. AdWords bidding algorithms must take into account the new conversion data, which is based on your new conversion settings. After two weeks, update the bid metric to ensure that you are no longer using Converted Clicks.


Monitor Conversions to View the Differences

Before changing the bid metric, however, you should monitor the Conversions, and see how their count differs from your current Converted Clicks. During this review, determine if Conversions are significantly higher than Converted Clicks. You may find this to be true especially if you are tracking multiple conversion actions or if you include cross-device conversions in the “Conversions” column.

According to Google, the difference between the two counts can be due to the fact that “each conversion action may receive a conversion after a click”. So, if you have conversion actions for both an email signup and a retail sale, and someone does both actions after clicking into your site, these will count as two conversions. While in the past, Converted Clicks would have counted this as a single converted click.


Change Your Bids

AdWords may lower your bids after you update your bid metric in an effort to stabilize your spend. If you wish to manually do this, especially if you find that your CPA or CPC cis rising, follow these steps to lower your CPA/CPC:

  1. Log into your account, and click on your campaign.

  2. Click on Settings.

  3. Click on Bid Strategy.

    1. Enter your maximum Target CPA.

    2. Enter your maximum CPC.

  4. Click Save.



Moving away from Converted Clicks is another step by Google to try and make their metrics more meaningful for consumers and to provide a more consistent experience. For marketers that have never used conversions before, however, you may have a bit of a learning curve. You should take to heart the recommended steps to prepare for the move, including changing the count and monitoring the conversions before you are forced to update all of your campaigns.

You should also prepare your stakeholders for the changes. Advise them that the reports may look slightly different, but that you’re still tracking towards ROI. Preparing yourself and everyone else for tracking conversions will decrease the number of headaches down the road.


About Misty Faucheux

20140725_0031Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on TwitterLinkedInInstagram and Flickr.


Advanced Reporting Template for Client Budget Tracking (It’s Free!)

PPC BUDGET TRACKING & PACING · 3-MINUTE READ ·  By Stephen Dawson on September 19 2016 


Your clients spend should be a key consideration when it comes to PPC management. Without a budget order, you don’t have the ability to place monthly caps on spend in AdWords. If it’s important to them, the line ‘Why are we 15% over spent this month?’ can make your heart drop.


Daily spend caps are a loose cannon in AdWords as Google cannot guarantee it limits spend to your cap. As Google puts it: “Your daily spend varies, and may peak at 20% above your daily budget to help your campaign reach its potential”.  20% variance is not good news if your client wants to work to a strict budget. You can set daily caps lower to anticipate spend peaks but then you’re in danger of under spending. We are left with the task of frequent daily budget monitoring.


As we would all wish for when it comes to PPC management, we want to focus less on the admin and more on the time that helps deliver the client’s objectives. Our client budget tracker removes the need for manual budget calculation and gives you the key insights you need on first glance. If you’re often on the move, our alert system will bring up any clients that need attention on a summary sheet. With supermetrics, you can schedule an automated email so this information is in your inbox first thing.






When you’re aware of what needs attention, you can use the budget calculation tool to set required daily spend. Given the 20% leeway, you may need to adjust this more than once throughout the month.


Set up


The sheet formulas will do their good work after you’ve done just a few setup tasks (no more than 5 minutes!)


  • After you select the template and you are directed to select which accounts to add, you will need to hold the Ctrl key down to select multiple accounts. The template will also work with one account

  • You will need to input each client’s budget into the budget column on the main sheet for the formulas to ‘wake up’

  • You can double click date input cells to bring up a calendar to select a date

  • Calculations for spend are based on the last full days spend and so a scheduled refresh need to be set up for each day at midnight. To do this follow the handy gif below:


Setting up supermetrics refresh2.gif

  • In the trigger menu you can also select ‘refresh & email daily’ and select the summary sheet to be sent you your inbox daily.


Things to know


There are some important things to know about the template that will make it more useful for you. Firstly, underspending and overspending warnings are defined by a 10% difference each way. If you want the sheet to be strict, you can change the formulas to work to a 5% difference. To do this you will need to unhide column D and change the highlighted numbers in the formula to 1.05:


=IF(OR(C12<0.9, C12 >1.1), “Requires Attention”, “”)


You will also need to change the formulas in the status bar for the budget calculator (in cells M10, N10, and O10). Replace 1.1 with 1.05 respectively.  


The sheet accommodates 100 clients but can be expanded by dragging down formula cells from row 110. Finally, the template is by no means set in stone. You can customise colours to suit your brand and change calculations. Once you’ve got your tracker just how you like it, you will be safe in the knowledge that your spends are well under control.




Even if you are lucky enough to have budget orders, tracking daily spend is still worthwhile to ensure you spend evenly throughout the month and hit your cap. Make sure you regularly check your projections to ensure you’re on track. Mondays and Thursdays are recommended (set your calendar reminders!) as to catch spikes in spend over the weekend and during the week. Stay vigilant, but you will have more time to focus on the things that matter!


Note: You can access the report with full instructions here


About ​​​Stephen Dawson

​​​IMG-20160828-WA0000-01Stephen Dawson is a PPC expert and analytics enthusiast at Fingo Marketing and a guest writer for​ ​Supermetrics. Inspired by meaningful data and report aesthetics he is a big fan of ​automation and bespoke layouts. Passionate for delivering an impact on bottom line objectives, especially for start ups and charities. You can find him on LinkedIn.​ 


A Step-by-Step Guide to PPC Account Structure: Campaign or Ad Group


PPC ACCOUNT STRUCTURE · 6-MINUTE READ · By Lindsay Shugerman on September 12 2016 

You need to add a new group of words to your Pay Per Click account. But should they become the newest Ad Group or do you need to create a whole new campaign? And the answer is…(drum roll, please!), it depends.

Not what you wanted to hear, right? The truth is, there is no “one-size-fits-all” answer. But thankfully, there are key factors that can help you make the right choice for your unique business or client. Here are some of the things you need to consider before choosing one or the other.



The Budget



Settings for your AdWords budget are done on a campaign by campaign basis. Although you can adjust bids for individual keywords or set a maximum cost-per-click for an ad group, there simply isn’t an option for setting a new, separate budget for an ad group.

Keeping your new words as an ad group within an existing campaign works well when you need to watch the total spend. That $300/day budget for Campaign Z will stay at $300 a day no matter how many ad groups you place within it.

But creating a new campaign for your new terms could easily increase your overall spend, unless you dial back the budget on existing campaigns to keep the daily maximum under control. And that change in the budget in an otherwise successful existing campaign could negatively impact your traffic and conversions.



The Location


Like budgeting, geotargeting is a setting at the campaign level, not the ad group level. Accounts that need to direct their messaging to people in several unique geographical locations need to create new campaigns for each geographic location.

Creating separate campaigns for different geotargets has another benefit. It allows you to use the same keywords for each location, so your best transactional or informational terms are not limited to showing only in a single top rated ad group within one campaign. This is a huge plus for companies with multiple, distinct locations within a country, or for multinational accounts.


The Campaign Type

Within Ad Words, PPC campaigns can be set to show:

  • Only on search, as text ads
  • On search, with additional features such as ad extensions
  • As mobile app engagement ads
  • On search as text ads, as well as in display
  • As call-only ads, which encourage searchers to call rather than click
  • As video-triggering ads

A new set of words may work well within the settings for an existing campaign, without limiting exposure or negatively impacting budget. In that case, creating a new ad group is probably be a good choice, if all other factors work within that campaign.

Other times, putting the new terms in a new ad group inside of a current campaign could be disastrous simply because of the campaign type. (And of course, disastrous is never the goal!)

Here’s an example:

Campaign W is set to search plus display, and is performing well in click-throughs, conversions and spend. A new set of words are added as a new ad group within W, but they’re much broader than the existing longer-tailed terms. Within a few days, the display clicks for the new ad group have run through the entire month’s budget for the campaign, without producing any new conversions. The broader terms simply triggered too many impressions and clicks for a display campaign.



The Importance of History

The ability to compare the performance of a given campaign over time is critical to business decisions or to client reporting in paid advertising. While adding and pausing ad groups is typical in the course of managing PPC, there are times when inserting a completely new set of terms as an ad group could make tracking a campaign’s performance over time difficult.

Before inserting a new ad group, consider the long term reporting needs. While filters can be used to present a more consistent view, some businesses or clients prefer being able to look at a campaign level over months or even years. New ad groups could distort that view.



The Words Themselves

Let’s take a step back for a moment to the structure of paid advertising.

With very few exceptions, it’s a best practice in paid search to build campaigns which describe a broad concept (such as a product group, a type of service or a geographic location, and then to develop ad groups that offer variations and refinements of that broad concept.

For example, a building contractor might set up a campaign for home remodeling, and then create ad groups for interior, exterior, bathrooms, kitchens, etc.

This structure allows the PPC manager to see how different aspects of the remodeling campaign perform against each other, and makes it easy to build out additional ad groups as search terms suggest new refinements.

Following this structure also makes it easier to review and evaluate ad content, landing page changes, and overall messaging within a single campaign. Adding a new group of words as an ad group within the campaign can function as a new yardstick for measuring keyword and ad copy value for a given campaign, rather than creating a situation where a mature campaign with multiple ad groups is being compared to a new campaign with a single ad group.

To use our example, if searches for bedroom remodeling needed to be added, creating an ad group under the remodeling campaign would allow the manager to compare performance across the various rooms, and pinpoint shifts in the specific remodeling needs of prospects by room, by season, by day of week, by time of day or even by ad or landing page copy. A new campaign would make those variances harder to spot and act upon.

On the other hand, if the contractor is now adding roofing to their services, a new roofing campaign would allow them to create targeted ad groups for types of roofs, roof repair and other related services. It’s a different kind of remodeling.



The Day To Day Management

All metrics and reporting considerations aside, the decision to add additional ad groups or new campaigns can sometimes come down to how much time the PPC manager or team has to dedicate to reviews, changes and updates.

In some cases, adding yet another ad group to an existing campaign will make it impossible to notice the impact of small changes in bids, edits to ads or revisions to landing pages. There is just too much aggregate data, and small improvements or drops are almost impossible to spot.

In other situations, there are already too many campaigns, and digging down into one after another is unnecessarily time consuming, especially if each campaign contains only one or two ad groups. It’s also challenging to compare the success of ad groups across different campaigns.

If daily reviews and adjustments are taking longer than the results justify, it may be time to back up and look at the overall structure before making the ad group or campaign choice. A PPC account which is clean, clear and as streamlined as possible should be the goal of anyone running a paid ad campaign.



The Checklist


It’s always good to end a complex discussion with a simple checklist. While there are many factors to consider, including some unique to your account, here is the quick-and-dirty overview:

BUDGET – How will the choice of ad group or campaign affect the overall budget?
LOCATION – Are the new words directed at the same geotarget as an existing, related campaign? Or this focusing on a whole new area?
CAMPAIGN TYPE – How will these terms function within your existing campaigns? Will they trigger the right kinds of responses?
HISTORY – How important is being able to track campaign performance over time? Will a new ad group significantly impact that, or have ad groups come and gone already?
WORDS – Are the words and phrases you need to add a refinement of an existing campaign topic? Or do they represent the first grouping of terms under a new broad topic?
DAY TO DAY – Will a new PPC ad group muddy the waters in an already complex campaign making small shifts impossible to spot, or will they clarify it so it’s easier to see trends? Will a new campaign streamline management, or make it more time-consuming without improving results?

The decision to place a new group of words into a PPC campaign or an ad group is seldom a simple one. But considering the impact on your business account or client’s success using these elements is the first step towards continued paid advertising success.



About Lindsay Shugerman

Lindsay Shugerman has been taking organic and paid search campaigns from struggling to success since 2006. She has worked in the corporate, non-profit and agency world, providing winning strategy and management for B2B and B2C search marketing clients in North America, the UK, Japan and India. Ms. Shugerman has taught SEO at Code Camps in Florida and Texas, and regularly leads PPC and SEO workshops for businesses, marketing teams and website owners. She currently works for a B2B agency in Austin, doing what she loves best: creating online marketing plans that work for her clients.











New AdWords Features Every Marketer Should Know


Responsive Display Ads and Price Extensions are two new AdWords features that can result in more dynamic ads.  Visually appealing ads along with more room for your messaging will result in a better ROI.  If you are unfamiliar with the recent changes from Google, take a look at a recent post on here about Expanded text ads before you dive into these features.


Responsive Display Ads

Responsive display ads were launched along with Google’s Expanded Text Ads in AdWords.  These ads are automatically generated from a headline, ad description, image, and a URL. This is a great feature to have for image heavy ads since AdWords will not support flash ads after this calendar year.


Ability to choose your image

Responsive ads are eligible to display across the entire Google Display Network (GDN).

Why this new format matters is because it allows advertisers to control the image shown in the ad rather than a default to the one Google pulls from a website which may not be the best reflection of the brand. This new format opens the door for professional looking ads for people who do not have design skills.  When creating a responsive ad, you will have the option to upload your image or let Google scan your site.

But there is some fine print because Google may still auto populate your ad with an image they select from your site rather than the one specifically uploaded. (I have not seen this happen yet, but understand it is possible). Even so, the responsive part is very appealing, knowing that an ad will adapt to where it is displayed and is easy to create.


More characters for  your ad

There are more characters available for the responsive display ad copy than even the expanded text ads.  This broadens the opportunity for messaging. The primary headline for responsive display ads is 25-characters with a second headline of 90-characters and description of 90-characters. The grand total of 205 characters for a single ad is a huge deal for display advertisers! Like with the old format, Google tracks the character count so you can easily see how many characters are left for your message when you write an ad.



There are some limitations of what can be done, one of which reminds me very much of Facebook. Text cannot cover more than 20% of an image which is something Facebook generally shuts down quickly with their ads. This limitation could be a challenge for advertisers with text heavy logos.  Other style requirements require advertisers to use only the recognized name of the business in the business name field and are not permitted to use animated images. Overall, you can see it is a huge improvement to Google Display Network (GDN) ads when comparing the old and the new format side by side below.



Price Extensions

Price extensions look very similar to a Shopping Ad simply because the price is displayed in the search result for these ads.


Currently, these are only eligible to display with mobile or tablet ads and only when the result is served in the top position.  This is definitely worth testing since, like other extensions, there is no additional cost to use extensions with an ad.  Of course, the obvious first step is to ensure you have a mobile friendly website. If you are not sure, use Google’s Mobile-Friendly Test to get a quick look at how Google views your website.


Getting started

Like other extensions in AdWords, these are created from from the Ad extensions tab by clicking red +Extension button. The basic information required is straightforward with a 25-character header, a 25-character description, price, and the landing page (Final URL). Selecting the Type will change the sample ads. In this example, you can see how a Services type extension would display in the top right.



Below is slightly different with an example of an Event type ad.



Best practices

As you can see in the above screenshot, multiple rows – price extensions – show different products and services with some basic information about the offer along with the price.  Be sure you are descriptive. I had price extensions in a campaign that listed pricing for an event as “Day 1”, “Day 2”, etc., which was disapproved by Google. You need to be more descriptive as shown above –  “Day 1- Bluegrass”.  Following best practices, the link on each extensions should take the visitor directly to the page with information about that specific item. If the multiple items in your price extensions are listed on the same page of your website, that works fine. There is no need to create a new landing page for every single item. The point is not to send people to a generic home page for everything.



Currently, Price Extensions are only available in English and for USD, CAN, GBP, EURO, AUD, and NZD currencies. Also, at least three extensions must be in the account before Google will potentially display that ad.

Advertisers can be granular at the ad group level or a little more broad at the campaign level. For example, with a limited time deal, a group can be created for a specific short-term promotion with relevant start and end dates.


There will be competition!

Competition will be fierce to get in this spot. The space alone makes this an incredible opportunity. Advertisers not only have their headline, message, and description displayed on the screen, but multiple lines depending on how many extensions are used. Searchers may see only that result when they search because those extensions push the organic listings down. If you are fortunate enough to have that top spot on mobile with price extensions displayed, you can qualify leads even before they click. Even though there are similarities to Shopping Ads, retailers running Shopping Ads should not use Price Extensions as a replacement. Instead, it will be interesting to compare the two options on mobile to determine possible differences between ads with Price Extensions compared to those created as a Shopping Ad.


Next Steps

These recent changes by Google cannot be ignored. Especially with Expanded Text ads since standard text ads cannot be created or edited after October. To implement these features in your account, start with an overview on this new format and make it a priority when you work on your AdWords account to get up to speed.

Once you have the basics down with your text ads, responsive ads are a no-brainer and are very simple to use. Those without graphic design skills can jump right into creating beautiful ads that respond to the user’s device.

And if you have a service or product with clear pricing AND a mobile friendly site, start to test this option and tweak it so you can get to – and stay at – the top of the search results on mobile devices. Although I do not immediately jump on every single feature that Google releases for AdWords, these are ones I am very excited about and know the results will be worth the investment.


About Tina Arnoldi

 Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

How to Make An Insightful AdWords Lead Campaign Report

ADWORDS REPORTING TEMPLATE · 6-MINUTE READ · By Ana Kostic on August 30 2016.

As a PPC campaign manager, I must choose the right amount of data to report and then present it in a visually helpful form. It’s hard to find the balance between the amount of data I need as the account manager and the amount of data the client or manager needs to make an informed decision or to follow up on.

These are two very different amounts of information that need to be placed within a single report, and it has taken me some time to adjust to this reality. In this post, I offer you an intermediate solution that I have found very helpful as a quick health check of an account for me and a very good monthly or weekly report template for a client or manager.

This solution is based on a template for lead generation campaigns, but it can be adapted for any type of campaign. The examples are based on a monthly review, but the time frame can be adjusted to the project needs.


KPIs and Simplicity: Basic Data to View What’s Important

To be able to perform, measure and meet our goals, we have to know what those goals are and which metrics will measure success. In this case, we start off with a table with very few metrics that reflect the health of the account in terms of business goals.

As first contact point, we want to know our traffic, leads, cost, CPA and conversion rate. We also want to compare these KPIs to those of the previous month, and the same month of the previous year, so that we can put our current numbers into perspective. The color scheme helps us see the performance very quickly.




I also like to use two charts as visual aids, one with the click and conversion (converted clicks) evolution and one with the conversion rate and CPA evolution. These help us put the evolution of the account data into perspective.





Monthly Evolution and Data Comparison

After the first table of KPIs, I like to start with some data tables. I like to get into the account details a bit to see some PPC evolution mixed in with the business goals.

In this monthly data table, we can see a monthly overview with all the main PPC metrics such as impressions, clicks, cost, CTR, CPC, average position, converted clicks, conversion rate, cost per converted click, conversions and bounce rate.




I want to clarify some of the metrics chosen for this table that might not be common ground in PPC.

Converted clicks and conversions: why have both metrics? When measuring leads, I like to add the AdWords tracking as the traditional “count every conversion” option and report on converted clicks for CPA purposes. But I also always like to have the converted clicks vs conversions data to make sure the “landing page” is doing OK. I know there are many ways to measure landing page performance and optimization, but I find that this data comparison is a very simple one for making sure things are going smoothly.

If the converted clicks and conversions are the same or very similar, then everything is OK. But if there is a big discrepancy between the converted clicks and conversions, this means that the landing page is experiencing some difficulties. It could be that the lead form is not simple enough and the user is going back and forth or reloading the page, or maybe the site is not fast enough and people get impatient, or any other issue. The data comparison is a good starting point for investigating further.

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I also always like to add the bounce rate in the PPC reports, as I believe it is a vital metric that affects the performance deeply. We do need to report on any variation, and we need to check for anomalies within the account in regard to this metric.

I like the monthly data table to show at least the last 14 months (when possible) so that we can easily see the trends of the past months, the past year, and the previous month and get a very good seasonality view. We need to keep in mind that the monthly evolution is very important, and we need to be aware of the months with high seasonality. In some cases, a drop in leads of 20% is a good metric if the previous year the drop was 40%. I have found that 14 months gives us the right amount of data.

I cannot live without the month over month (MoM) and year over year (YoY) comparison tables for the same reasons. We must always put a number into perspective by taking into consideration the previous month and the previous period. This is such a vital point for me that it was a key basis for my decision not to use many reporting tools (before supermetrics) because I was simply unable to compare the same data with the previous month and the previous year.

These give us all the information we need at a simple glance. If you want, you can add some conditional formatting to the percentage variations to see the numbers even clearer.




Network and Device

I put network (campaign type) data and device type data into two very simple tables that allow us to be aware of both dimensions.

I do this for the network (campaign type) data because it’s a dimension we can easily forget about and it is a very easy way to see the search and display data at a glance.

I do it for the device type data because there is no need to stress out the importance of the mobile traffic and we need to be aware of the mobile and tablet numbers. This is more important now that Google has promised us more bidding options for all the devices.




These are just two quick glances at both dimensions. If we see some odd numbers or variations, we can investigate further on our end, but I find there is no need to dive deeper into detail for a status report.


Campaign Data

Obviously, we could not forget our main core structural information in our PPC campaign, which is the campaign data. I like to keep the account data at the campaign level and not dive too deeply into the ad groups, keywords or ads because I have found that going any deeper just gets people very confused and we just drift off into PPC details and off the actual business goals that we need to act on.

Of course, a PPC account manager needs to dive into all those details and be very aware of them and analyze them, but that is exactly the account manager’s job, and not the client’s/manager’s. I have found that, at this point, it is just too much information that is not helpful at all to have on a goal-driven analysis conversation.

For the more detailed analysis and optimization, I have separate reports that dive into each of those.




Product Data Table (with AdWords Labels)

I have always had my doubts about the location of the product data table, and I have still not decided if it should go before or after the campaign data table.




In most cases, we do not have one single business goal, one single CPA or one single campaign type, and we need to report and be aware of the performance of all these specifics. In this example, the table is based on different types of products.

We can have several campaigns for one single product, or we can have one campaign with several ad groups, each one for one product type. It is very difficult to have a perfect structure where we have one campaign per product or objective, so this is where AdWords labels come to our rescue.

All we need to do is label each campaign or ad group with the data they represent, and we will have a very neat table by label that shows all the information per product.

And, again, once we see how the products are performing, we can check our data more deeply on a separate report if needed.


Geographic Data

The geographic data table is another one of those indispensable tables I always like to have ready, as this information could be even more meaningful to the client or manager than to me as the account manager. Of course, we have to take action on this geographic data in terms of bid optimization, but we can also see emerging markets or test expanding regions that could mean a lot of potential business in the future.




Visual Help, Graphs and Color Schemes to Help Identify KPIs

Along with the data tables, it is very important to include a lot of visual help because not everyone sees patterns in the same way and, most of the time, the tables can be a bit overwhelming.




Conversion and CPA MoM Variation

In order to be able to easily see the MoM trends and act on any variations, I like to add the conversion and CPA variation data into the network (campaign type), device type, campaign data, product data and geographic data tables, as you can see in the last two columns of those tables.





About Ana Kostic

Ana-KosticAna Kostic is a PPC Expert and Consultant at Bigmomo and a guest writer for Supermetrics. Expert in PPC campaign design and implementation, as well as optimization focused mainly on the return of investment and goal consecution and especializad in international and multilingual campaigns. Passionate about PPC, Online Marketing, Reporting and Data Analysis. You can find her onTwitter or LinkedIn.


How to Effectively Use Naming Conventions in Google Analytics


Naming conventions can make the difference between collecting easy to understand data and data that is very hard to use.

Not only web analysts, but also digital marketers need to understand how the different sections in Google Analytics are structured. This is of key importance to deriving greater insights from your data.

In this post I will share my ideas on naming conventions and hierarchies for your account structure, campaigns and events.

By following a few best practices you will save a lot of valuable time for doing analysis instead of losing time just wandering through your account.


1. Account Structure

Every user can have access to one or more accounts, properties and views in Google Analytics.


Account Structure


In total you could have access to: 100 x 50 x 25 = 125.000 reporting views. Not that this will be ever the case, but you can imagine how important it is to name your administrative section in a proper way. Read this support article for more information on account structure hierarchies.



Most of you will have access to one or a few website accounts. For the “account name” I recommend to use either the name of your organization or website. In my case:

  • Organization: Online Metrics
  • Website: online-metrics.com

If you have access to multiple accounts, try to stick to using either the organization name or website name but not both. It’s all about being consistent!



It’s a best practice to use numbers if you have multiple properties in your account. Let’s assume you have three different environments: production, staging and gtm (test property). You could use the following property structure:

  • 1. Production (UA-123456789-1)
  • 2. Staging (UA-123456789-2)
  • 3. GTM (UA-123456789-3)

This setup makes it more easy to sort on your properties. Remember to use the lowest number for the property that is used most often. By doing this your most used properties will show up on top of your account.



You might only have access to one account and one property. However, very often multiple views are set up to collect different data sets in a separate environment. Here are some rules to incorporate:

  • Use the property name in your view name (applicable if you have multiple properties).
  • Use numbers to distinguish between different reporting views.
  • Use single digits if you are sure you won’t create more than eight or nine reporting views.
  • Use double digits if you might create more than nine reporting views.

This is an example setup for a “production” property:

  • 1. Production all data (no filters)
  • 2. Production all data (IP filters)
  • 3. Production internal traffic
  • 4. Production desktop only
  • 5. Production tablet only
  • 6. Production mobile only

Note: you might want to ask your colleagues to set up a clear naming structure in the admin section if you don’t have the access rights to take care of this. At the end it will help everyone to find the data in the quickest possible way. Setting the user permissions in a smart way is another thing you should do to keep in control!


2. Campaigns

Campaign tracking is another crucial piece in getting meaningful, well-structured data in your Google Analytics account.


Campaign Tracking


I like to describe campaign tracking as: “The endless process of structuring and measuring your online marketing campaigns so that you can analyze and optimize your online traffic sources and outcomes“. The words in bold refer to:

  • Endless process: you need to do it right today and tomorrow.
  • Structuring and measuring: you need to use parameters to structure your campaign URLs.
  • Analyze and optimize: target and optimize subsets of website visitors.
  • Channels and outcomes: allocate your online marketing spent to the best converting channels.

On default, Google Analytics can correctly measure direct traffic, organic traffic and incoming referral traffic. AdWords traffic can be added to this list as well if you get the integration between AdWords and Analytics right.


Naming Convention for Five Parameters

Google Analytics incorporates five parameters you can use to build a campaign tracking URL:

  • utm_medium: identify a medium, e.g. email, affiliate or organic (required).
  • utm_source: identify a source, e.g. yahoo, zanox or amazon.com (required).
  • utm_campaign: identify a campaign, e.g. fall promotion or summer contest (required).
  • utm_term: identify the keywords that drive traffic.
  • utm_content: differentiate ads or links that point to the same URL, e.g. newsletter links.

Best practices:

  • Start with identifying the medium for your campaign link; this is generally the highest level in campaign tracking.
  • Create your links using a spreadsheet (for many links) or use the Google URL builder add-on (if you have just a few links).
  • If you use a spreadsheet, make sure to add the responsible person and start (and end) date of a campaign.
  • Dont’t wait to add campaign tracking parameters to your spreadsheet until you forget about it.
  • Involve every person in marketing so that they know how campaign tracking works.
  • Make sure not to pass any personally identifiable information (PII) in a campaign tracking parameter.
  • Set up Google Analytics lowercase filters on campaign parameters to automatically handle small mistakes (e.g. using Email instead of email).
  • Thoroughly review your campaign tracking procedure and spreadsheet on a quarterly basis (at a minimum). Is everything going well or do you need to make some modifications?

What if your current campaign tracking looks like a mess? This is an example of a bad setup:


Bad naming conventions


Without doubt this is going to lead to interpretation problems. Who knows in this organization what these media definitions mean? Probably just one or two persons.

In this case I recommend to set up a channel grouping – together with the person who is responsible for creating this medium structure – to retroactively bring the right context to your data.

This great post by Annielytics is very useful if you want to learn more about channel groupings.

What if you make a “mistake” in your future campaign tracking definitions?

Let’s assume one of your colleagues uses “e-mail” instead of “email” to tag a few newsletters. First of all, you can’t undo any media information that is passed into Google Analytics.

However, if you are on time, you can quickly modify how Google Analytics measures the actual campaign.

Therefore you need to use a “Search and Replace” filter:


E-mail replace filter


You can set up a few “Search and Replace” filters in advance. So that any future mistakes are corrected automatically. The difficulty is that you need to predict the kind of mistakes that you or your colleagues are going to make!

Without doubt “campaign tracking” is one of the most (maybe the most!) important features in Google Analytics to get right.

You want to analyze and optimize your campaigns in the best possible way and this is impossible if you make a mess of your campaign tracking structure!


3. Events

There is one more feature I want to shortly discuss: event tracking.

You can directly implement events hardcoded on your website, but in most cases I recommend to implement events via Google Tag Manager.

Events can be used for literally anything that describes an interaction or a simple event happening on your website (other than a default pageview).

The three common labels are:

  • eventCategory
  • eventAction
  • eventLabel
  • eventValue

It’s completely up to you how you want to pass this information into Google Analytics. But, here is how I usually go about it:

Event Category – the name of the group of similar events you want to track. For example: Downloads, Outbound Links or YouTube Videos. Make sure to always use the “plural” form to keep your naming consistent.

Event Action – the name of the type of event you want to track for a particular element on your website. For an embedded YouTube Video this could be: play, pause, 0%, 25%, 50%, 75% or 100%.

Event Label – the name of the web page element, whose users’ interaction you want to track. For an embedded YouTube Video this could be the title of the video.

Event Value – the numerical value assigned to the event you want to track (optional).

It depends on the involved website and exact informational needs, how I determine the final structure.

However, keep in mind that preferably you shouldn’t structure your event category groups in one account in a different way. Usually there are quite a few events implemented on a website. So people will get lost if you create a very unlogical structure.

Finally I like you to create a spreadsheet for your event tracking structure as well. Especially if you deal with a larger website, this makes it much more easy to keep track of what is being measured and where!


Final Thoughts

As you have seen, hierarchies and naming conventions are crucial in Google Analytics. They determine how effectively you can spend your time in Google Analytics.

Of course, it is very important to create a good structure for everything you do. But of equal importance is keeping track of what you do. Simple spreadsheets built and shared via Google Drive will do.

I hope you have picked up a few new methods to organize your Google Analytics account in a better way!

What are your thoughts? Do you already use naming conventions in Google Analytics and in what way? I am happy to hear your opinion!


About Paul Koks

Paul Koks

Paul Koks is an Analytics Advocate at Online Metrics and a guest writer forSupermetrics. He is a contributor to industry leading blogs including Kissmetrics,SEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

Why every SEO analyst should use Google Search Console

Google Search Console · 4-MINUTE READ · By Tina Arnoldi on August 16 2016 ·

Webmaster Tools naturally sounds like it’s for the web developer on your team, not you as a marketer or SEO analyst. When it was renamed to Google Search Console in 2015, it became clearer that the tool was not just for web developers; it is equally useful for marketers.

If you are responsible for monitoring organic traffic to your website, this is a great addition to your toolkit. With it, you can learn how Google views your site, how searchers find you organically, and key areas regarding your website that need to be addressed.

We have an earlier post describing how to get more than 90 days of Search Console data with the Supermetrics Google Drive add-on, Data Grabber, or with Supermetrics Functions. Here we will step back a bit and review what this tool can do for you as a user of Google Analytics.

How to start: check if your Search Console account is already connected to Google Analytics. You can check this by visiting Acquisition > Search Console in your Google Analytics account. If you do not see any data, follow the prompts to connect the two products. If you are not able to do this, it is because you do not have enough rights in Google Analytics or will want to contact your Analytics Administrator.

Once you are done with the setup, let’s go through what Search Console can help you. 


1. Learn which keywords Google thinks describe your site

Content marketing is tough. There’s  a lot of noise so you want your content to be found without keyword stuffing.

Naturally you think your site is based on what you write. You have a product or service and provide content for that theme. However, part of being found depends on how Google “sees” you. To view one of the signals they use, visit Search Console and look at Google Index  > Content Keywords.

In the below example for a counseling site, there is not a significant amount of content for Google to use at all. Although the keyword “counselor” is the top keyword, it only shows up three times.  

Line four below – therapy – seems equally important to a counseling site since those words can be used interchangeably, but that word is also infrequently used.  This is not uncommon with sites that tend to be more brochureware. If you have a content heavy site though, this would be a concern if your top words were not listed.


search console ccc ontent.png


2. View search queries that bring people search to your site

I am  still mourning the “not provided” keywords we have now in Google Analytics. Fortunately we can get some of those words back with Search Queries in Search Console.  

The below screenshot shows queries for a marketing site which indicates a number of people are searching for help regarding Twitter and this particular site occasionally comes up.  

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Although it’s great for a site to come up in search, if the site’s primary service is PPC or SEO with very little consulting on social media, it’s time to refocus the content on the site to include more relevant keywords for that business.


search console 360 queries.png


3. Access your site metrics and dimensions

Yes, there’s a ton of data in Google Analytics already. What is great about Search Console is that you can gather detailed data on search queries mentioned above.

Search Console displays the clicks, impressions, click-through-rate (CTR), and position of terms in organic search. In addition to these search query metrics, there are also dimensions which include pages, country, device type, date, and type of search.


4. View links to your site

Google Analytics users already know this data is available in Acquisition > Source/Medium.  There is detail on the domains linking to a site, the total number of links, pages others link to, and the anchor text that links to your site.

Check if there are pages you expect to see but are missing in this view. It could be you had a link that was removed from a referring site or is a broken link.  

You’ll want to invest some time on a backlink strategy to increase the links to key pages.


5. Check your site’s mobile friendliness

It’s been more than a year since Google rolled out the mobile-friendly update and as mobile use continues to climb, having a mobile friendly site is no longer optional.

When you check this in Search Traffic > Mobile Usability, hopefully you will have a message similar to the below. This indicates your site is in good shape and works well on mobile devices.

If your site does not have the stamp of approval like the below message, you will see specific messages about issues, such as a small font size or use of flash.  Those fixes need to be a high priority on your to-do list.

You can also how your site performs on mobile with Google’s Mobile-Friendly Test before any site edits and check it again after you have optimized the site.


search console mobile usa.png.

6. Check for errors

If you build it, they won’t necessarily come.  But if it is built right, they will eventually see what you have to offer.

Building and maintaining a quality site means pages you build can be found by Google.

If a page has a 404 – not found – error, you can see the referral for the page that is a 404. This is incredibly helpful because it may show a link from your own site which is easy to fix.

Even if you believe your site is in perfect shape, take time to check this in Search Console. When new pages are added to a site and old ones removed, it is very easy to overlook every single page on the site.  

You may also discover that pages are not even showing up in search results. Watching for, and correcting errors, is a key element in providing an excellent user experience.


7. Review pages crawled and download time

Crawl Stats will give you metrics about Googlebot activity over the previous 90 days.

The number of pages crawled should increase as Google discovers the pages on your site.

The time spent downloading should be lower over time.  

Page speed is crucial both for engines and for people. In the today’s internet world, several seconds for a page to load is too long. The searcher has already moved on to another result before your page is even viewable.

Below you can see a significant change over time (in a good way) for a site.


search time downloading.png


Although there’s even more to Search Console, these are some key features that make a great case for adding Search Console to an SEO analyst’s toolkit.

Spend some time in there doing an audit and share the findings with your team. You may be surprised to find simple changes you can make that will have a significant impact on your site’s performance.

Start by addressing any site problems with your webmaster, such as mobile usability, 404 errors, and download time.

Next connect with your writers so they can integrate some “content keywords” in their future posts.

And finally, remember that using the Search Console is not a one time activity. Plan to check in here at least once a month, possibly more depending on your site traffic.



About Tina Arnoldi

 Tina Arnoldi is Analytics and AdWords Qualified and one of the few people in the United States recognized as a Google Developer Expert(GDE) for marketing. Her agency, 360 Internet Strategy, is also a Google Partner. You can learn more about her on LinkedIn

How to Make the Most of Google AdWords’ Expanded Text Ads

Google Adwords Expanded Text Ads · 6-MINUTE READ · By Misty Faucheux on August 8 2016 ·

Leveraging the Potential Power of Double Headlines and Longer Descriptions.

After months of  announcement, Google has finally released the Expanded Text Ads (ETA) for AdWords campaigns, and now marketers have more room to advertise their goods and services. You, however, need to know the potential and potential risks of these new ads. We’ve pulled together a guide to help you understand the new ads and what you should be doing now to prepare for the permanent change.


Understand New Guidelines

The new expanded text ads are optimized to fit the screens that most people use nowadays – mobile. Google states that they updated the text ads because “longer ad headlines are more useful to mobile users because they provide additional information about your business before they click your ad”.

The new expanded text ads include:

  • Two headline fields as opposed to the single one on the standard text ads, accommodating up to 30 characters each versus 25.

  • One long description field (up to 80 characters versus 35*2) as opposed to two short description fields.

  • One display URL section. No more need to input both a display and final URL. The ads will just pull your display URL from your final URL.

  • Two “Path” fields (up to 15 characters each). The path fields allow you to add two or more of your keywords to your website’s domain – but they don’t have to match the final URL. For example, if your final URL is http://supermetrics.com/blog/#!quickly-improve-google-analytics-skills, your display URL could be http://supermetrics.com/google/analytics-guide.


Use the Path Fields

While the Path fields may be optional, don’t ignore them. Always take advantage of this opportunity. Why?

Well, as marketers, we’re constantly instructed to use our top search keywords in our ads to improve the likelihood of someone clicking on it. While sage advice, sometimes it’s difficult to ensure that the main keywords are in every ad because maybe we’re testing messaging or simply don’t want every ad to sound alike.

The amazing part of the Path fields is that you can still use your top keywords without ever having to put them in the headlines or description. You simply add them to the display URL.

To use the new Path fields, simply:

  • Go into your Campaign and Ad Group.

  • Click Ads, +Ad and then Text Ad.

  • Start filling out your Final URL, Headline and Description copy.

  • In the Path section, Add Keywords.

  • Save ad.


Don’t Turn Off All of Your Current Ads

While standard text ads may no longer be accepted after October 26, that doesn’t mean that you should rush to turn off all of your current ones. In fact, a recent study by Merkle reviewed early results of click-through rates on the new expanded text ads, and the results are mixed.

  • 16-percent lift in CTR for median site and ad groups on desktop

  • 4-percent lift in CTR for mobile phones

  • 8-percent lift in CTR for tablets

For the latter two, this is far lower than the 20-percent increase in CTR that Google promised.




Tip: Add a few new expanded text ads into your mix, and see how they do. Don’t convert all your ads to the new format. You may suffer drastic drops in clicks.

Hopefully by the time the standard ads go away, we’ll see improvements here.


Don’t Try to Recycle Your Old Ads

You’re going to have to write new ads. Yes, it’s going to be a pain, but it’s necessary.

You can’t just add more words to your current ads and hope for the best. Your ads need to make sense. Plus, the goal of the new ads is to give advertisers more room to create more compelling copy.

WordStream recommends

  • Using the extra characters to bolster your existing offers and to improve CTAS

  • Updating your ad extensions since they might be redundant with the new ad copy.

These ads eliminate the need to create mobile-only ads since they allow you to speak to people across all devices. You can still make mobile-only ads, but it’s not necessary.


Experiment with AdWords Script

 In case you don’t want to new ads from scratch, check out this AdWords Script tool. It provides a “starting point” (make note of that) for new ads by fetching the title tag of a website and breaking it up into two lines of 30 characters.

Most title tag lengths are between 50 and 60 characters – which makes them rather ideal for headlines.



The tool also grabs the website descriptions and converts those into the new, longer description. The problem with the latter, however, is that most descriptions are more than 80 characters. The script simply truncates the sentence at the last full word before it goes over 80 characters.

HoweverI’d recommend using this for inspiration only. Especially if you’re having trouble coming up with new ads for a client or stakeholder, the script could provide some brain fodder. Don’t use it beyond that.


Preview Ads Before Launching

With the standard text ads, you can easily start a thought or sentence in one description line, and finish it in the next. When the ads come up on desktop, the page is long enough to make it a single description. On mobile, it’s neatly broken up into two lines.


With the new text ads, however, you need to be careful with this. Allowing the headlines to run into each other, or one of the headlines into the description can lead to some goofy-looking ads.



Preview the ads carefully before the launch to ensure that your headlines are two distinct sentences. AdWords provides a preview of both the mobile and desktop versions on the right-hand side of the setup screen. If you’re generating them in AdWords Editor, you’ll have to go into AdWords to preview the ads.



Update Ads in AdWords Editor

Since its launch, AdWords Editor has been one of the best tools to update multiple campaigns, or copy ads, ad groups or whole settings into a new campaign. Google has released an update to the AdWords Editor that lets you make and edit the new expanded text ads.

  • Download the latest version of Google AdWords Editor.

  • Open up Editor, and then your account if you have multiple.

  • Select the Campaign and Ad Group.

  • Choose Ads-> Expanded Text Ads.

  • Click on Add expanded text ad.

  • Post your new changes to AdWords.



Update Your Reports Built with Supermetrics

The AdType for the expanded text ads in reports is EXPANDED_TEXT_AD so you can distinguish them from current ads. You can choose to include the following fields into your AdWords reports:

  • HeadlinePart1
  • HeadlinePart2
  • Description
  • Path1
  • Path2

To ensure that you’re capturing all the latest statistics, refresh the data in your Supermetrics reports by either scheduling a daily refresh or hitting the refresh button.



Since the ads only recently launched, we can’t say whether they will be click-through saviors or simply another dud in the history of online marketing. You should, however, start experimenting with the ads and see what is working for you and/or your clients.

We will all be pushed to use these in a few months. So, don’t wait until the last minute to begin testing the new ads to see what is and is not working. And use these tips since they’ll help you navigate the new world order of AdWords.



About Misty Faucheux

20140725_0031Misty Faucheux is an Integrated Online Marketing Specialist at Faucheux Enterprises and a guest writer for Supermetrics. She is a digital marketer, specializing in SEO, SEM, content marketing/writing and social ads. Misty helps companies develop a cohesive online marketing strategy that directly addresses their overall business goals and objectives. You can find her on Twitter, LinkedIn, Instagram and Flickr.


10-point checklist for a Perfect Google Analytics Setup

GOOGLE ANALYTICS SETUP · 11-MINUTE READ · By Paul Koks on August 03 2016 

In the last 10 years I have audited dozens, or probably even hundreds of Google Analytics accounts. Most setups are far from collecting meaningful and reliable data.

This post will equip you with tools and tips to improve your setup in the next few days. I will discuss 10 different items that are important to get right from the start.


1. Account Structure and Raw Data View

Google Analytics allows you to set up one account with multiple properties and reporting views. Read this support article if you are not completely familiar with it yet.

There is one golden rule here, always keep one data view without filters and/or other modifications. This is called a raw data view.

Filters and their effect on your historical data cannot be undone. Start out with segments and move to filters once you get more experienced with segmentation in general.

Every company should set up a few data views including raw data view and one view with IP address filters. This reporting view guide will tell you all you need about setting up different views for your business.


2. Bot Filtering

In all your reporting views – except your raw data view – you need to turn on the bot filter setting.

It can be easily located in each of your reporting views under the “view settings” tab:


Bot Filtering option (turn on)


In addition, make sure to set up a hostname filter on your domain(s) as well.


Include supermetrics.com filter

This will prevent you from irrelevant/unreal traffic showing up in your account.

Google Analytics is doing a lot to ensure that the least amount of spam traffic reaches your account. At a minimum I recommend to take the above steps to enhance the quality of your traffic from your end.


3. Goals

The very important and specific actions you want your website visitors to take on your website are called conversions or goals.

You can find your goals both in the reporting and admin interface.

Goals in Admin Interface

Goals admin interface I

In the example above, many goals are not recording (turned off) and might have been in use in the past. Two goals record the same number of conversions and in total there are three goals set up in this reporting view.

Step 1: define your most important goal(s) on your website: macro goal(s).

Step 2: define your supporting goals on your website: micro goals.

Step 3: decide upon which goals to implement in Google Analytics. Please refrain from implementing goals with very high conversion rates (“easy” conversions) in your main reporting view. This will make your overall conversion rate metric useless.

Step 4: implement and test your goals in Google Analytics.

Setting up goals is one of the most important activities you can do in Google Analytics. Well-defined goals will help you find out what works on your website and what doesn’t work. You can cross-segment your goals to many different dimensions in the reporting interface. Another trick is to use the Google Analytics API and export your conversion data to an external tool for further analysis.


4. Goal Value

Don’t set up goals without a goal value. You should always apply a goal value to your goal; the only exception is e-commerce transactions. These transactions have already a value attached via the revenue metric. Goal valueHere a few guidelines:

  • Start with applying a value to your most important goal (this is most often the easiest to do).
  • Apply other values (that you can make an estimation for) for the other, minor goals.
  • Use relative goal values for the goals you are not sure about.

At the end it is all about getting an estimation of how your website is performing in different channels, on different landing pages etc. and compared to your costs.

Setting up goal values will unlock a few different powerful metrics of which page value is one of them!

Goal values help you to analyze and optimize your website efforts. In addition monetary values are much easier to discuss internally than absolute numbers. Think about the difference between saying: “In total we have 3.000 macro and 8.000 micro conversions or we have generated Ç 250.000 of value for our organization (estimation)”. What would your boss prefer to hear?


5. Personally Identifiable Information

Personally Identifiable Information (or PII) is strictly forbidden to collect in Google Analytics. 

Make sure to check your account for any PII since Google Analytics is allowed to terminate your account if any PII is collected.

It happens quite often that this information is submitted via search boxes and from fields. And it won’t be the first time that I see email addresses appearing in a Google Analytics account.

I recommend to read this article by Google as well:

Pay extra attention if you have User Id’s implemented. Violating the PII laws can easily be done in this case.


6. Bounce Rate

You are doing great if your overall bounce rate is below 30%. However, if your bounce rate is below 20 or even 10% you need to be suspicious.

It could be that your tracking code is fired twice on your pages. Your website visitor cannot bounce when a second pageview is automatically triggered.

Three tools to help you debug your implementation:

Less often I come across extremely high bounce rates. This can be due to unfiltered spam or ghost traffic or an improper Google Analytics implementation. You might end up with a very high bounce rate if you haven’t tagged many of your pages.

Example of where high bounce rates might occur: The majority of the people that visit your website are clients. When they click on the “sign in” button, they are redirected to another environment (which is not tracked by Google Analytics). You have outbound link tracking enabled, but the link is measured as a non-interaction event. In this case your bounce rate might be very high because of these settings.

In order to prevent your bounce rate from becoming flawed, you need to tag all your website pages and make sure that your tracking code is only fired once on each page.


7. (Not Set) Values

Checking (not set) as a value for your key dimensions is another thing you should definitely check in your Google Analytics account. 

The appearance of a high percentage of (not set) in a particular dimension almost always indicates a tracking issue.

Here are eight dimensions you should check:

  • Landing Page (Behavior > Site Content > Landing Pages)
  • Page Title (Behavior > Site Content > All Pages)
  • Hostname (Audience > Technology > Network)
  • Source and Medium (Acquisition > All Traffic > Source/Medium)
  • Organic Keywords (Acquisition > Campaigns > Organic Keywords)
  • Paid Keywords (Acquisition > Campaigns > Paid Keywords)
  • Browser (Audience > Technology > Browser & OS)
  • Geo Location (Audience > Geo > Location)

Read this in-depth article on (not set) by LunaMetrics and apply the tips to your Google Analytics account. Please note that there is one browser (Safari (in-app)) that always has a high percentage of (not set):


Safari (in-app) - (not set)


You don’t have to solve this one.

It is extremely helpful to automate these checks, especially if you are working for multiple companies as a digital analytics consultant. Supermetrics for Google Drive can eliminate many of these tasks for you and speed up your (not set) implementation check.


8. Content Reports

How many “unique” URLs are visible in your “all pages” report? You might spot thousands of pages although you know your website counts far less unique pages. This is the case when there are a lot of query parameters present.

Here is a fictional example:

  • supermetrics.com/tools/grab/?id=19204035035
  • supermetrics.com/tools/grab/?id=19204035011
  • supermetrics.com/tools/grab/?id=19204035025

The id at the end of the URL is the unique identifier. This will make Google Analytics register three different pages on default. In reality this is the same page with only one technical parameter present.

Here are the steps you need to take:

Step 1: sit down and investigate your content reports for an overview of these parameters. Make a list (in Excel).

Step 2: talk to your web developer and make sure that your list is complete.

Step 3decide upon the parameters and make a list of non-essential parameters (parameters that don’t add any value to your analysis)

Step 4a: add the non-essential parameters to your view settings.


Exclude URL query parameters


The following step is only recommended if you want to filter out all query parameters, both now and in the future.

Step 4b: add a custom filter to filter out all query parameters.

Exclude All Query Parameters

Filtering out non-essential query parameters will make your content reports much more accurate and actionable. You can choose to pursue step 4a or step 4b. For less experienced Google Analytics users I recommend to start with step 4a first.


9. Annotations

Do you keep track of your marketing campaigns, technical website changes and other changes that might have a big impact on your website numbers?

If not, you really miss out on providing context for your data analysis.

To make things easier for you, Google Analytics has a built-in feature called annotations. Here are five tips when using them:

  1. Be explicit about what it means (you have 160 characters for each annotation).
  2. Keep in mind the people that will be reading them in the future.
  3. Record both online as well as offline marketing campaigns.
  4. Record any updates (e.g. adding filters) and/or site issues.
  5. Record any external events that might have an impact on your traffic.

One last thing, don’t overdo. These annotations need to add value, so very minor changes should not be added to avoid confusion in your organization.

You can set them up in the reporting interface or via the admin interface.

Annotations via Reporting Interface

Annotations Reporting Interface


Annotations via Admin Interface

Annotations Admin Interface

I prefer to set them up in the admin interface if I want to add multiple annotations at a time. Please also note that you can only set up future annotations via the admin interface.

Annotations are a great help in analyzing your data in context. I recommend to make them publicly available so that your team members can benefit from this information as well.


10. Traffic Sources (Source/Medium)

Another crucial thing to get right is campaign tracking.

Head over to Acquisition > All Traffic > Source/Medium.

Does this report section look clean with sources and media that you understand and can relate to? Or is it a mess with not much saying names that make you confused?

In the first case, great! You belong to the minority of people that get this set up right. In the second case, you have some work to do!

Google Analytics allows you to structure all your campaigns and traffic sources in a meaningful way. Direct traffic, organic traffic, referral traffic and AdWords traffic (if AdWords is integrated with Google Analytics) is taken care of automatically, but the rest of your channels need special attention. 

This extensive guide on campaign tracking is definitely worth checking out if you want to learn more.

Tracking your campaigns in the right way makes your all traffic sources report reliable and powerful. Once you understand the basics of how to set this up, it is highly recommended to use a spreadsheet to keep track of everything in a better way.


Concluding Thoughts

When it comes to setting up Google Analytics in the right way, there are a lot of things to keep in mind. Start with checking and applying these 10 tips first and you will be well ahead of the pack.

The more attention you spend to this phase, the more reliable your data becomes and the higher are your chances that you can extract actionable insights from your data.

What are your main challenges with getting the Google Analytics setup right? Do you apply a particular strategy when setting up your Google Analytics account?


About Paul Koks

Paul Koks

Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including KissmetricsSEMRushWeb Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

How to Build a Bot with Supermetrics and Google Sheets

PPC/SEO SLACK BOT  · 8-MINUTE READ · By  Matthew Guay on July 28 2016


Ever wished you could pull up your spreadsheet data right inside your favorite chat app? Perhaps you’re discussing this month’s sales with your boss, or are trying to remember what a recently popular Tweet said during a team chat. Supermetrics has already pulled that data into your spreadsheet—but you don’t want to go search through a spreadsheet right now.

What you need is a bot that’ll find the data for you, and put it right into your chat app. Bots are simple robots that, like Siri and Google Now, can find information for you on the fly. The only difference is, you can type in commands in chat apps like Slack or via SMS messages, and bots will find the text you need and send it back to you in seconds.

Here’s how you can build a Slack bot to find info from your analytics and social media data in Google Sheets without leaving your chat—and if you want, you can use the same steps to make a bot for Twitter, HipChat, SMS, or any other text-powered app.


Building a Slack Bot for Your Spreadsheets

You only need three things to build a bot:

– An app with your data
– A chat app to talk to the bot
– An integrations tool to connect your data to the chat app

You likely already have a Google Sheets spreadsheet filled with data from Supermetrics—that’s the perfect tool to use with your bot. And team chat app Slack is a free, easy-to-use tool for both staying in touch with your team and talking to bots.

Then, to connect the two, app integration tool Zapier is the perfect tool for the job. It can connect hundreds of apps—including Google Sheets and Slack—to save data to your spreadsheets, notify you when it’s changed, and find data in your spreadsheet without you having to open it.

Let’s use all three to build two bots that can find data from our spreadsheet: one to find social media info, and another to look up detailed analytics or ad data. We’ll use a Slack slash command bot—one of the types of bots you can build in Slack. Essentially, type a slash followed by your command—say, /sheet to search your spreadsheet—to talk to the bot.

For more details about Slack Bots, be sure to check out the full Slack Bot tutorial on the Zapier blog.


Find Social Media Data with a Bot

So, first, make sure you have a spreadsheet with data from Supermetrics that you want to search through from Slack. I’m using a spreadsheet with recent popular Tweets about Google Sheets.




Then, open your Slack integration settings at slack.com/apps/build, click Make a Custom Integration, select Slash Commands, then add the command you want to use. I’ll use /sheet, but you can use any command you’d like.




Slack will then open a settings page, which we’ll come back to in a second. First, though, we need to make a Zapier Webhooks integration that Slack can send your bot’s text to. For that, create a Zapier account, and click the Make a Zap button in the top right.

There, choose the Webhooks by Zapier app, and select Catch Hook. Click Continue, then copy the Webhooks URL that Zapier gives you.




Now, go back to your Slack settings from before, and paste that Webhook link into the URL field on that page. If you want, you can add a name and icon to your bot as well. Then, save the settings.



You’re ready to test out the bot. Just open Slack, type your slash command, followed by what you want to search for in your spreadsheet. I want to find recent Tweets from Google, so I typed /sheet Google.



Now, go back to your Zapier integration page, and click Continue where you left off. It’s time to connect your spreadsheet to Google Sheets, to search for the item you want.

To do that, select Google Sheets in the app picker, then choose the Lookup Spreadsheet Row action. Connect your Google Sheets account, and choose the correct spreadsheet. Then, select the column of your spreadsheet you want to search, and click the + icon beside the Lookup Value field and select the Text element from Slack to give Zapier the item you’re searching for.



Test that, and Zapier will find a row from your spreadsheet with the correct data. Now it’s time to send that data back to Slack, and make your bot actually work. Click the Add a step button, and this time select Slack as the app and Send Channel Message as the action.

Connect your Slack account, then it’s time to make your bot smart. In the Channel option, select the Use a Custom Value option then click the + icon beside Custom Value and select your channel name from the Slack Webhook.

Then, add your Message text. You can type in anything you want, or click the + icon to pull in data from your Google Sheets spreadsheet.




Test the Zap and turn it on, and you’ll get notified of the item you were looking for in Slack.

Now, next time you need to find something from your spreadsheet, just type it with your command into Slack, and your Zapier-powered bot will find it for you.




Dig Into Ads and Analytics Data With a Bot

Now, perhaps you don’t need to find a Tweet. Instead, you need to dig into your company’s analytics data and find out exactly how many pageviews you got in May last year, or the clickthrough rate on last month’s ad. To build that bot, you’ll use the exact same steps as above, only this time we’ll use a spreadsheet with analytics and ad data.

Say we want to search the sheet for the views on a specific month’s ad campaign. We’ll start out by pulling the ad and analytics data into the spreadsheet with Supermetrics. Make sure you have a consistent name for your months in the leftmost column, and that you’ve named each of your data columns to make them easy to lookup.




Now, use the same steps as before to make a bot in Slack. Only this time, when you send a test message in Slack, we’ll be searching for a specific month from our spreadsheet. So, to find last month’s ad views, we’ll enter:

/sheet 2016|06

That uses the same year and month style that we’ve used in our spreadsheet, to make it easy to find the month we need.

Now, let’s find that in the spreadsheet. As before, add a Google Sheets Lookup Spreadsheet Row action to your Zap, and this time in the Column setting we’ll select Month column. In the Lookup Value field, click the + icon on the right as before, and this time select the Text field which has the month from our query.




Then it’s time to send the correct data back to Slack. As before, add a Slack Send Channel Message action, and select a custom channel using your webhook data.

Now it’s time to write your Slack message. Add any text you want, and click the + icon to pull in the ad view data that Zapier just found from your spreadsheet. Or, you could bring in any extra info you want: the clickthough rate, cost per click, or anything else you need.




Next time you’re discussing your ad campaigns in Slack, you can grab the latest data in seconds with your bot.





Spreadsheets are powerful tools—especially when you combine them with add-ons like Supermetrics and integrations from Zapier. With built-in functions, you can use the data those tools put into your spreadsheet and build your own powerful tools without any code.

Want to turn your analytics data into a custom dashboard, or make a CRM that pulls in info about your contacts and sends emails automatically—all from a spreadsheet? Then check out Zapier’s new free eBook, The Ultimate Guide to Google Sheets. It’s everything you need to know about Google Sheets, from the beginner steps to sort and format your data to advanced tips that let you import data from websites, automatically format your spreadsheets with Google Apps Scripts, and much more.

Download a copy —and set up your own integrations to make your Supermetric-powered spreadsheets even more powerful.



About Matthew Guay

a8d41c6e-dad4-4cee-99bc-767d4d181d71Matthew Guay is a content marketer on the Zapier team. He lives in Bangkok, and loves writing, photography, information architecture, and finding new ways to get apps to work together. Get in touch with him on Twitter @maguay.



3 Common Mistakes In Presenting Your PPC/SEO Data (And How To Fix Them)



You’re very proud of the insights you just obtained from your PPC/SEO work, and you can’t wait to show them to your stakeholders or customers on your coming presentation.


Will you just copy and paste your data graphs on your slides or will you take the extra time to create tailor-made charts and find the optimal words to present them? Taking a shortcut might not be the best idea.


No matter how proud you are of your reports, your job is not done yet. Put yourself in your audience’s own shoes for a moment, and you will discover some potential problems. There are at least three big problems:



1.       Graphs don’t show the insight per se

If you show a graph as it is—for instance one of the magical reports Supermetrics creates—you will force your audience to gain insight by themselves. Their job is not to analyze your graphs and get insight. It’s yours, as a data analyst. C-suite executives or customers will not have either the time or patience to dig deep into the graphs. They all rely on you as the expert who can bring light out of a sea of data.


2.       PPC/SEO reports don’t show the context by default

Beware that in the analyst’s mind are both the insight and the context in which the conclusions were drawn. In contrast, a decision maker looking at your report and its insight can see only a part of the whole picture. The context is missing unless you present it explicitly. Only then, your audience will be able to understand how you gained that insight and ultimately will either agree or disagree with you. The context is usually outside the report: industry benchmarks, other marketing channels on your organization, qualitative data, etc.


3.       Looking at heavy graphs and listening to a presenter is multitasking

All of us have attended presentations where the speaker showed text-heavy slides while speaking to us (to make things worse, often reading the slides). The result: we had to choose between reading what was on the screen and paying attention to her words. Human brains can’t do both things simultaneously, can’t multitask.

Similarly, heavy graphs force your audience to multitask while listening to you. Instead, simplified graphs can be quickly understood and followed in sync with your words. Elon Musk’s Tesla Powerwall Keynote is a great example of showing the right dose of data in the slides.

Lack of insight, lack of context and heavy graphs, put altogether can make your presentation a complete failure. Do your best to avoid these problems.



Now, how can we transform your brilliant insights into an effective and successful presentation?

Consider the following three elements:


1.       Craft storytelling

The main problem with numbers is that often they are difficult to relate. That’s why it’s crucial to make them as concrete as possible. Going a step even further, a story will help you to illustrate your findings in a more emotional and sticky way.

Chip and Dan Heath, the authors of “Made to Stick” summarize the idea in this memorable quote: “Data are just summaries of thousands of stories – tell a few of those stories to help make the data meaningful.” Go and rewind back, find a story to illustrate each insight.

Imagine that you have to show “200% increase in social traffic during Q1” in a slide. First, begin with the story telling “It all started when our colleague Laura posted a photo of our building completely covered by snow, and it went viral on Twitter.” Then move on and explain the data.


2.       Do not copy and paste. Re-draw your graphs yourself

If your charts and tables look awesome in MS Excel, they will probably look bad in your presentation slides if you just copy and paste them. OK. The obvious solution would be using default charts’ templates by PowerPoint or Keynote, right?

Not so fast. After hearing a number of presentation design experts, I still haven’t heard anybody who recommends using the default charts that PowerPoint or Keynote provide as the best option. Maybe for a school assignment they are OK, but not for serious business. Just forget about them.

The best solution is to re-draw your graphs yourself. This will be really beneficial for you. As re-drawing can be an intensely manual work, this will force you think twice before making an exact copy and you will rather draw a simplified version. The resulting simplified graph will make your presentation a thousand times more effective. You can draw simple graphs with the tool of your choice, either online [some suggestions here] or offline (such as PowerPoint itself).

In cases where you really need to copy and paste a specific graph from MS Excel to PowerPoint, Lea Pica’s best practices will be of help.


3.       Simplify the message, both words and numbers.

This also applies to creating a great dashboard: you can’t just fill it with numbers and numbers. You have to use words. Some data analysts recommend that a dashboard should contain 50% words. However as we well know, it is easy to go from one extreme to another and fill a presentation slide with words. Let’s aim for the perfect balance.

One of the most valuable techniques is the “McKinsey title” which consists in writing the insight as the title of your chart. For example, instead of “Referral Traffic” write on your slide’s title “Twitter was the best referral channel in June.”

Your ability to communicate the results and recommendations of your hard work analyzing data will make a big difference in how you are valued. You can really inspire action. That’s why it’s well worth learning the skills of presenting data like a star!


About the Author

SONY DSCOscar Santolalla Host and Producer of the public speaking podcast Time to Shine. Oscar has spent more than three years as a Product Manager in the software industry. Either onstage or on blogs he advocates making technical presentations and product demos that engage and inspire. He is currently writing the book Create and Deliver a Killer Product Demo

AdWords Conversion Tracking: 7 Major Factors That Impact Performance



As marketers we all rely on some form of AdWords conversion tracking to optimize campaign performance. 

We get our heads stuck in data for hours trying to make the best possible decision. We argue over low-performing keywords with clients and colleagues. 

In the end our decisions are based on conversion data that is reported inside of Google AdWords.

But in our day-to-day work we all forget one important factor: conversion data is always biased and incomplete.

This article highlights seven major factors that have a big impact on performance.


Google AdWords Attribution Models


Attribution Models (Source: AdWords Help)

The default attribution model for AdWords conversion tracking is last-click attribution (you can now change that). That means if there are multiple AdWords clicks before a conversion, only the last click will get conversion credit. 

Based on last-click attribution keywords which are at the beginning of the research process will tend to show a higher cost per conversion. This is because people might initially find your website through a broad search term but then refine their searches further as they become more informed about what they actually want. 

Very specific keywords are typically close to the buying decision and are therefore more likely to be the last click before the purchase. These keywords will show a better performance based on last-click attribution. 

If you are running campaigns targeting generic keywords (“car repair” etc.) as well as a campaign targeting your own brand name (“tom’s car repair”), the brand campaign can “steal” some of the credit that should actually go to the generic campaigns.

Check out the AdWords attribution tool to understand the implications of different attribution models on your cost per conversion (in your AdWords account, click on Tools -> Attribution).


AdWords Conversion Tracking vs Google Analytics Import

There are two main ways to track ad performance in Google AdWords:

  1. AdWords conversion tracking

  2. Importing goals or transactions from Google Analytics

Most marketers do not realize that there are significant differences between AdWords tracking and imported Google Analytics goals/transactions. Two of the main differences relate to conversion attribution and date of attribution.


Conversion Attribution

Both AdWords and Google Analytics use last-click attribution. The main difference is that Google Analytics uses last-click attribution across all channels whereas AdWords tracking does not consider other channels.

This means that if there are multiple AdWords clicks before the conversion, AdWords will credit the last click with the conversion. However, Google Analytics will look at all traffic sources (including organic traffic, referrals etc.) and credit the source that generate the last click before the conversion. So even if there were five AdWords clicks before a conversion, Google Analytics will only give AdWords credit if the last click before the conversion came from AdWords.

In practice, this means that importing Google Analytics goals/transactions into AdWords will often result in a lower number of reported conversions.


Date of Attribution

 Google Analytics records conversions at the actual date and time when they occur. On the other hand, AdWords credits the conversion to the date of the last click. So if someone clicks on an AdWords ad on March 19 and and returns to the online on March 23 to eventually buy a sweater, Analytics will record the conversion for March 23 whereas AdWords would record it on March 19 (when the last ad click happened).

One of the major consequences of this is that conversion numbers based on AdWords tracking can still increase retrospectively for as long as you set the cookie duration. If you check last week’s conversion numbers today and the again in 30 days from now, you will typically see the number of conversions has increased due to the fact that AdWords credits the last click not actual transaction date with the conversion. The additional conversions that happened in the meantime are referred to as post-conversions.

For a full comparison of the two  tracking systems check out these Google articles:

  1. Comparing Analytics and AdWords conversion metrics

  2. Import Google Analytics goals and transactions into AdWords


How Cookie Duration Affects AdWords Performance

 The standard cookie duration for AdWords conversion tracking is 30 days. In other words, conversions that happen within 30 days after an AdWords click will be credited to that last click. The cookie duration can be set anywhere between 7 and 90 days. Conversions that happen after the cookie window will not be credited anymore.

 Here’s an example why it’s important to choose the right cookie duration for your business: While working with one of my eCommerce clients, we realized that a significant amount of conversions happened near the end of the standard cookie window. After increasing the cookie window from 30 days to 90 days, we ended up tracking an additional 20% conversions.

 To set the right cookie duration for your business, check the ‘time lag’ report in your AdWords account. From your AdWords interface, click on Tools -> Attribution -> Time Lag.

Time Lag.png

The example above shows an average time lag of 5.88 days to a conversion. In this case the standard cookie duration of 30 days would be sufficient.

If your time lag report shows a lot of conversions near the end of the standard cookie window, make sure to increase the cookie duration. The longer you choose your cookie duration the more post-conversions AdWords will tend to credit.

Check the next point for more details on post-conversions.


Implications of Post-Conversions 

As discussed earlier, standard AdWords tracking will credit the last ad click with a conversion. As a result, AdWords conversion numbers can increase retrospectively. That means if you check your conversion numbers for last week today and then check the same time period in 30 days from now, the conversion numbers will normally have increased.

These additional ‘post-conversions’ obviously didn’t actually happen during the week that you initially checked but the last AdWords click prior to the conversions happened during the same week. The amount of post-conversions depends both on your cookie duration and the type of product or service you are advertising.

A longer conversion time lag and cookie duration implies a higher amount of post-conversions in your AdWords account. Therefore you need to keep in mind that AdWords performance data for any given time period is only final after cookie duration. So in most cases 30 days from the last day of the time period you are looking at.


Implications of Phone Sales 

By default AdWords doesn’t track phone sales or enquiries. That means AdWords doesn’t get any credit for any conversions that happen on the phone. 

Depending on the business, phone sales/enquiries can make up 20%, 30% or even up to 50% of the total conversions. You need to take this into account when you check the cost per conversion in your AdWords campaigns. 

There are plenty of phone tracking solutions out there that integrate with Google AdWords. What you can do is implement one of them for a couple of months to find out the ratio of phone conversions to online conversions. The ratio is typically very stable so once you have determined it you can just give AdWords the extra credit for it.


Before-And-After Comparisons

 When we analyse the effect of our AdWords optimizations we typically do a before-and-after comparison.


AdWords performance: compare the same time periods whenever possible.

The right way to do a before-and-after comparison is to compare the same time period across years, i.e. May 2015 vs May 2016. The wrong way to do it is to compare last week to this week or April 2016 vs May 2016.  This is because all businesses have an underlying seasonality that affects performance throughout the year (typically more than any other factor).

Second, when you are comparing time periods you need to ask yourself whether the tracking setup was the same. Where you tracking the same type of conversion? Was the cookie duration the same? Has the tracking setup changed from AdWords to Analytics import?  Just one change in the way you track performance will make a performance comparison like this unfeasible.


Actual Revenues vs Tracked Revenues


 How to spot changes and  irregularities in your tracking setup over time

This article covered a lot of different areas that can change your conversion data significantly, This last point is not a factor impacting performance but rather a tip to spot changes or irregularities in your tracking setup over time. A great way to assess accuracy and changes in your conversion data is to compare it to hard sales figures.

The screenshot above shows an example of how to do it:

  1. Create a spreadsheet and add your actual monthly revenue in one column.
  2. Then add two columns for revenues tracked in Google Analytics and Google AdWords. Calculate the percentage of tracked revenue to total revenues next to each of them.

Obviously these ratios will be nowhere near 100% because AdWords doesn’t generate all of your revenue and because not all of the sales happen online. However, the ratios over time can easily highlight if there was a problem or change in your tracking.


Final Tips and Thoughts

We have discussed various factors that can change your AdWords performance data significantly: attribution models, tracking setup, cookie duration, phone sales, post-conversions etc.

Here are a few specific examples:

  • Last click attribution will show different results than first click attribution

  • AdWords tracking will report different results than imported goals/transaction from Google Analytics

  • A longer cookie duration can increase (i.e. improve) your AdWords performance by capturing additional conversions

  • A sudden shift towards more offline conversions (e.g. phone sales) can make your AdWords performance look worse

  • AdWords conversion data can improve retrospectively due to post-conversion

So what’s the main take-away here?

  • Keep things in perspective. Remind yourself that AdWords conversion data is based on your specific setup and often doesn’t show the full picture.
  • Keep track of any major changes with respect to your tracking and settings.

So when you have to make an important AdWords decision, take into account external factors and look at your data from perspectives using the AdWords attribution tool.


About Stefan Maescher


Stefan Maescher is an advertising professional and blogger at stefanmaescher.com. He helps businesses maximize their ROI online by using data-driven optimization strategies. He also teaches his best insights in an online course called AdWords Profits Shortcuts.


How to Jumpstart Your Reporting with Supermetrics Template Gallery

We’re really lucky to have such great reporting templates from places like Google Analytics Solutions Gallery to help our own reporting and analysis of digital marketing initiatives.

This got us thinking … What if you could have the same easy and useful templates for your reports with Supermetrics as well?

So our team worked very hard in the past three months to put together a few example KPI reporting templates, to help our new users jumpstart their reporting. If you’ve already been using Supermetrics, you may get inspiration from our templates and how you can report different marketing metrics as well.

You probably already have the Supermetrics Google Drive add-on installed. So let’s cut to the chase and dive into the tutorial.  

Two ways of accessing the templates

Option 1: From the add-on (recommended)

  1. Open Google Sheets and launch the add-on

  1. Go to drop-down menu Add-ons -> Supermetrics -> Template gallery

  1. Choose the template you want and click on Add template

  1. Choose the Google Analytics account and click on Insert template

  1. Enjoy your beautiful dashboard!

Option 2: Directly with a URL


I’ll use our Traffic Dashboard template, which shows Google Analytics traffic source data, as an example. Please copy the URL below


  1. Create a new Google Sheet and launch the add-on

  1. Go to drop-down menu Add-ons -> Supermetrics -> Template gallery

  1. Scroll to the bottom and find Custom template

  1. Paste the URL you’ve just copied to the text box, and click on Add template

  1. Choose the Google Analytics account and click on Insert template

  1. Enjoy your beautiful dashboard!


Other templates


Here is a list of all the templates we offer for now. We’ll be adding more in the coming months.


Year-on-Year Comparisons – Google Analytics year-on-year comparisons



Country Comparisons – Google Analytics country comparisons



US State Comparison – Google Analytics US state comparisons



Heatmap – Google Analytics data by hour & day of week



Traffic Source Bubbles – Google Analytics traffic source bubble chart



Cohort Analysis – Google Analytics retention & cohort sales analysis



Social Media Tracking



Pro tips


If our report templates don’t exactly fit your needs, there are two options you can manipulate the reports.

Option 1: Edit the data for a chart

  1. Unhide the hidden columns where the data is

  1. Go to the data table you want to edit and click on the Modify button on the right

  2. Say instead of the trend of users you want to see the trend of new users. Simply go to the Select metrics section, delete Users and select New users, and then click the blue Apply changes button on the top



Option 2: SupermetricsQueries sheet


A more geeky approach is modifying queries directly in the SupermetricsQueries sheet. This way you can make changes more efficiently.

  1. Open up SupermetricsQueries sheet

  1. Go to the query you want to change and click on the grey Modify button in sidebar

  1. Or you are familiar with our queries, you can type in the changes directly into the cells. Say you want to change the time range to H1 2016. You can put custom to the Data range type cell, 2016-01-01 as the Start date and 2016-06-30 as the End date

  1. At last, click on the blue Refresh button in the sidebar

Try out our templates and let us know what you think. If there is any template that could be helpful for you but we don’t offer yet, please leave a comment below or shoot me an email at zhao.hanbo@supermetrics.com


Happy reporting 🙂


How to Quickly Improve Your Google Analytics Skills



What steps do you take to master Google Analytics? Relying on one strategy is not your best choice. Take a structured, well-balanced approach to boost your Google Analytics skills.

Google Analytics is a tool that is used by the majority of online businesses worldwide.

What if you would find a way to improve your skills so that you go from beginner to intermediate user? Or even from intermediate user to expert?

In this post I will reveal a well-thought-out framework that will help you to improve your Google Analytics skills in a quick way.

And the good thing is, you can apply the strategies to other areas as well.5-step framework

  1. Study: read, watch listen to Google Analytics learning material.
  2. Ask: ask questions to improve your understanding of Google Analytics related topics.
  3. Share: share your knowledge with others.
  4. Practice: theoretical knowledge is one thing, practical experience is even more important.
  5. Reflect: reflect on what you have learned and whether your approach works or not.

From this point on I will share more details on each of the topics above.

1. Study

Reading from and listening to other experts is one of the best ways to start if you want to enhance your skills.

There are many great resources out there that can fasten your learning curve.


I recommend to add these blogs to your reading list if you prefer reading over listening:

  1. Analysis Ninja
  2. Analytics Pros
  3. Cardinal Path
  4. E-Nor
  5. Insights Blog
  6. Jeffalytics
  7. Loves Data
  8. LunaMetrics
  9. Occam’s Razor
  10. Official Google Analytics Blog
  11. Online Behavior
  12. Online Metrics
  13. Optimize Smart
  14. Simo Ahava
  15. Web Analytics World

And of course you should read the Supermetrics blog as well. 🙂


There are dozens of Analytics books out there.

Here is a list of five books to start with:

Note: I love to read books every now and then, the only disadvantage is that they can easily get outdated because of rapid developments in the (Google) Analytics industry. However, most foundational processes stay nearly the same.


There are people that love reading, but maybe you belong to the category that likes to listen and/or watch.

If that’s the case, I recommend checking out the following resources:

Google Analytics Academy

Google Analytics Academy Resource link: https://analyticsacademy.withgoogle.com/.


Here you can find tons of interesting videos on Google Analytics.

Google Analytics Filters YouTubeMake sure to use a longtail search term (and not just “Google Analytics”) if you want to learn more about a specific topic.

Analytics Course by Jeffalytics

In my opinion, one of the greatest courses currently out there is offered by Jeff Sauer. His course is very in-depth and covers beginners, intermediate as well as advanced topics.

Analytics Course by Jeffalytics Resource link: https://www.analyticscourse.net/.

Measure School

Another great resource you definitely want to check out is Measureschool.com.

Measure School

The founder of this website is Julian Juenemann.

At Measure School you can take both beginners as well as advanced courses on Google Analytics and Google Tag Manager.

Further I recommend to check out his YouTube channel as well. It’s fully packed with useful resources on GTM.

Market Motive

If you want to educate yourself and be guided by the brightest minds in the field, I recommend to visit the website of Market Motive.

They offer both guides course as well as self-paced courses on a wide range of digital marketing topics.

The faculty includes big names as Avinash Kaushik (Web Analytics) and Brad Geddes (PPC).

In addition, I recommend to visit events, attend workshops or even go to one of the larger (international) conferences out there.

Meeting peers is a great way to strengthen your network, learn a lot of new things and have fun!

Note: don’t forget to concentrate on enhancing your skills in related areas as well. It’s not just about Google Analytics. That’s a tool and even more important is your general understanding of doing analysis and optimizing website outcomes based on data.

2. Ask

You don’t want to do it all on your own, do you?

There are numerous ways to get Google Analytics support for your query.

It’s all about giving and taking. Help others and you will receive support back. If you are relatively new it’s very logical that you ask more than the help you can offer. Later on you will be on the other side.

Here are five resources I like to share to get an answer to any questions you might have:

  1. Google Analytics forum (great place to ask questions on a wide range of topics, you can expect a quick response to your query)
  2. Google Analytics Help Center (tons of useful information on a wide range of GA topics)
  3. Google Analytics Plus community (with more than 100.000 member and expert moderators another great place to ask your questions)
  4. Google Search (your best friend for very specific queries)
  5. LinkedIn community (with over 80.000 members a fantastic opportunity to network with peers and get help)

In addition, you can ask questions via Twitter, Facebook or any other platform you use.

Getting an answer to your question is not that difficult. Just reach out to others in a friendly way and they will help.

3. Share

One of the greatest ways to thank others, is by paying back to the community.

I started my own blog back in december 2012. And was involved with digital analytics for over five years at that time.

A long story short, I have written over 100 posts on digital analytics and Google Analytics on my blog and other industry leading blogs in the last three years. It’s so rewarding when you can help others on their journey.

And something very important to understand:

The best way to improve your Google Analytics skills is by teaching it.

I really believe that the key in learning something new or from going from intermediate to advancer user is by actually teaching it. So it doesn’t matter whether you want to learn Google Analytics or Google AdWords or anything else. When you start teaching others you will learn faster. Try it and let me know how it goes!

A lot of people do make YouTube videos to help others AND themselves. By simply putting together a YouTube video they can more quickly enhance their skills.

You don’t have to start your own blog, but simply helping others whenever you can, is already a great thing to do. And the digital industry will benefit from your efforts as well!

4. Practice

You can read tons of books, listen to podcasts every day and ask questions on a regular basis, but if you don’t put things in practice, you won’t improve your Google Analytics skills that quickly.

When you learn something, you need to apply it to really master it.

Back in school you had to prepare or answer questions via case studies. And now you need to do something similar.

Consultant or Analyst In-Company

You might be working for a company or are outsourced as a consultant.

In both cases, if you learn something new and want to master it, apply it!

Example: you find out how to automatically export data via the Google Analytics API. Don’t stop here, because you can do something more.

  • Ask yourself how you can make the data export more useful.
  • Maybe you can build a dashboard in line with the KPIs and online objectives of the company you are employed.
  • Or maybe you can teach your colleagues the same set of skills so that they can master it as well.

This is the most easy way. You have already and direct access to an environment where you can put your skills in practice.

Start an Ecommerce Business

Is there a particular product you want to sell? You could think about starting a small ecommerce business.

Start an ecommerce business

This 10-points checklist will definitely help you out.

Starting a small business is a fantastic method to boost your Google Analytics skills.

Your data delivers great input on how things are going and whether you need to change your strategy, modify your product assortment or in general, where you should focus on.


I assume you don’t have your dream job yet, but you want to put your knowledge in practice. There are quite a few (non-profit) organizations out there seeking help from someone like you.

Here is an example:Google Analytics VolunteerOr maybe one of the people you know runs a small business, but doesn’t know anything about digital marketing or digital analytics. Offer your help, it will be greatly appreciated and you will fasten your learning curve.

There are a lot of opportunities out there. Reach out and you will find dozens of ways to actively works on your skillset.

5. Reflect

If you find out that something works, great and keep going. However, make any necessary changes if you find out that something doesn’t work.

It’s the same with starting a business. You will invest more money in products that do sell than in products that only cost you money.

I recommend you to reflect as least one time per month on how things are going.

Answer the following questions:

  • What method worked well in the last month?
  • What method didn’t work as expected in the last month?
  • What activities do I like most and work the best for me?
  • What activities don’t feel good to me?
  • How can I improve and learn and share more in a better way?

This is how to turn yourself into a Google Analytics master in record time! And as a bonus, you can apply these tips to other areas in life as well.

This is it from my side. I hope you have enjoyed reading this article!

Any questions or thoughts? I am happy to read and answer them in the comments section.

About Paul Koks

Paul Koks

Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including Kissmetrics, SEMRush, Web Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

Supermetrics now connects with Twitter Ads (And How to Get It Running With 5 Clicks)

Today, we’re happy to announce Supermetrics is now fully integrated with Twitter Ads. Another step that lets you gain a more comprehensive view on your mix of paid marketing channels. With this new connector, you can easily import Twitter Ads data into Google Sheets and Excel to analyze your cross-channel campaign performance data, in conjunction with Adwords, Facebook Ads and Bing Ads.
As our other connectors, our Twitter Ads connector allows you to keep your dashboards up-to-date by scheduling automatic data refreshing. And you can always share your results by scheduled emails. This integration is live today in all of our reporting tools: Supermetrics Google Drive Add-onSupermetrics Data Grabber for Excel, and Supermetrics Functions.

Getting started with Twitter Ads in Google Sheets, with just 5 clicks

If you’ve used our Google Sheets add-on, you can choose to add Twitter Ads data to your own reports by running queries, just like with our other data sources. But we’ve also prepared a Twitter Ads dashboard to help you jumpstart. In this short tutorial below, we show you how to easily use our Twitter Ads connector to build a campaign objective tracking dashboard.
1. Open up Supermetrics sidebar in Google Sheets, and choose Twitter Ads in the list of data sources
select Twitter Ads
2. Authorize Supermetrics to access your data
authorize in Twitter Ads
3. Choose the right Twitter account, and then click Insert The Template
Insert The Template
Enjoy a cup of coffee while we’re working hard to process your Twitter Ads data 🙂
refreshing queries
Voilà, you’ve got your Twitter Ads dashboard. Easy peasy, huh? 
And wait, there is more. Scroll to right in the spreadsheet and you can find a table for each campaign type, Engagements, App Installs, Followers, Leads and Video.  Give it a try and let us know what you think!
If you haven’t tried Supermetrics yet but love to automate your reporting and focus on analysis, the easiest way to get started is to take advantage of the 30-day free trial of our Google Drive add-on.

10 Ways to Segment Google Analytics Data for Greater Insights

Segment Google Analytics · 9-MINUTE READ · By Paul Koks on May 31 2016

One of the keys in finding actionable insights, is to segment your data and visitors. Raw data without context doesn’t tell much.

But wait a second… Before even thinking about analyzing your Google Analytics data, you should always define a business question first. What are you trying to solve or improve? Without it, your analysis or deepdive won’t be effective.

I assume here that you took the time to define a business question and are ready to examine your data in more detail. One way to do this, is by applying segmentation techniques.

In this post I will describe 10 methods I often use to segment the data for greater insights.

1. Date Range

Segmenting on date range or time period can be extremely useful.

For example, one month ago you launched a new feature on your website. You want to quickly see how your website performs this month compared to one month ago.

To keep it simple, you just want to see the basic numbers on your website.

Step 1: open the reporting overview.

Step 2: navigate to Audience >> Overview.

Step 3: press “d” and then “m”.

Step 4: press “d” and then “c”.

Step 5: investigate your report.

Audience overview report

In this example I have used shortcuts to quickly create the report that I need. You can review the shortcuts by pressing “Shift” and then “/” (the forward slash / question mark function).

2. Primary Dimension

Metrics and dimensions are the building blocks of almost all reports in Google Analytics.

So how can you distinguish between them?

  • A dimension is a characteristic of an object that can be given different values —> a dimension describes data
  • A metric is an individual element of a dimension which can be measured as a sum or ratio —> a metric measures data

A dimension comes very much in handy when you want to segment your data.

To show you an example, I will open the source/medium report in Google Analytics.

Segment primary dimensionIn this overview you can judge the performance of your channels based on the source/medium definition.

It is clear that in terms of bounce rate and pages/session, the referring site masseymarathon.com performs very well.

3. Secondary Dimension

Secondary dimensions go one step further than primary dimensions. They allow you to combine two dimensions when analyzing your data.

For example, you want to analyze source/medium and compare it to region (country).

Step 1: click on secondary dimension.

Click on secondary dimension

Step 2: select “country” as dimension.

Select countryStep 3: investigate your report.

Primary and secondary dimension

4. Tertiary Dimension

The tertiary dimension is based on a trick not many people know about.

It allows you to segment your standard report based on three different dimensions in record time.

Step 1: click on a primary dimension; in this case I click on “bing / organic”.

Click on primary dimension

Step 2: change the primary dimension to “country”.

Change primary dimension

Step 3: use the secondary dimension as a tertiary dimension.

Tertiary dimensionI use two or even three dimensions to quickly understand what’s going on on a website in relation to a business question that I defined first.

It literally just takes minutes to segment the data in this way.

However, if you find yourself doing this on a regular basis, make sure to consider using a look like Supermetrics instead! It can save a huge amount of time if you use it in the right way.

Note: by clicking on “source/medium” in the navigation bar on the left you can quickly return to the default report (only a primary dimension selected).

5. Basic Table Filters

Another good option for segmenting your Google Analytics data are table filters. You have basic and advanced table filters.

  • Basic table filters allow you to segment on the primary dimension.
  • Advanced table filters allow you to segment on one or more primary and secondary dimensions including metric conditions.

Let’s assume you want to see the organic “source/medium” combinations that drove traffic to your website.

You need to fill in “organic” in the “search filters box” to get the data that you want:

Organic traffic sourcesExamples of when this can be useful:

  • Compare different PPC terms that include one specific word or phrase.
  • Compare landing pages that include one specific directory.
  • Compare different banners belonging to the same campaign.

Note: you can fill in both regular expressions as well as plain search phrases in the search filter box.

6. Advanced Table Filters

Advanced table filters are very useful if you want some more flexibility when segmenting on your data.

Here is an example report setup with a secondary dimension applied:

Advanced table filter 1Now you need to define the information you want to see in your report:

Advanced table filter 2I have included two definitions here:

  • Landing Pages that contain the phrase “12-week”.
  • Bounce Rate is less than 80%.

Here is the report (hit “apply” first):

Advanced table filter 3It returns the “source/medium” and “landing page” combinations based on the rules that I set before.

In the top right corner of the screenshot you can see “Advanced Filter ON”.

Note: by setting up a custom report (which we will discuss later) you can create reports with more dimensions. You can do this by setting up a flat table. This is a static, sortable table that displays data in rows.

7. Plot Rows

The “Plot rows” function can be a great help if you want to take a more visual approach in segmenting your data.

Step 1: select the groups of data you like to plot.

Select rows to plot

Step 2: select “plot rows”.Plot rows exampleIt enables you to visually compare different rows of data in a quick way. In this case you can conclude that the portion of organic traffic to the website doesn’t differ much in the selected period.

Best practices:

  • Make a trend graph over a longer period of time. Day to day numbers don’t say much.
  • Aggregate your data on a monthly basis so you can better judge the trends.
  • Export your data to better analyze the numbers and take more accurate conclusions.
  • Use the Google Analytics API and a suitable application to do more advanced analysis.

8. Segments

One of the best ways to segment your data is by using the segments function in Google Analytics. It’s a great way to isolate and analyze subsets of your data.

You can work with predefined segments or come up with a unique segment that you create by yourself and perfectly suits your business and the question you want to answer.

Let’s assume you want to analyze a few reports for mobile traffic only.

Step 1: click on “add segment” in the reporting interface.

Add Segment

Step 2: select “Mobile Traffic” and deselect “All Users”.

Mobile traffic appliedStep 3: investigate your report.

Mobile traffic performance

Quick insight: bounce rate “Mobile Traffic” is above website average.

Keep in mind:

  • There are built-in and custom segments; I recommend to use them both!
  • Be careful when saving segments; you have the option to add them to one or more views at the same time.
  • You are allowed to compare up to four different segments at a time.
  • Make sure you share the segments with your team.
  • Be aware of data sampling risks.

9. Custom Reports

Custom reports are another very powerful feature in Google Analytics.

They help you to create a report that best answers your business question. Simply by selecting the metrics and dimensions that you need.

Without going in all depth, I show you a quick way how you can master custom reports:

“Update existing reports if you are relatively new to this feature.”

Step 1: select one report as the template of your choice, e.g. “source/medium” report.

Step 2: click on “Customize” button.

Default report into custom reportStep 3: click on “Customize” button.

Modify custom reportThis template helps you to understand how custom reports are built and what options you have if you want to modify them.

In short: select the closest template to your needs and modify it so that it exactly shows the data that you need.

Note: you can also build a custom report from scratch or download one from the solutions gallery.

10. Admin Filters

The first nine segmentation options that I discussed are ok to use for anybody, regardless of your experience with Google Analytics.

However, admin filters are not like that. Filters that you set up in the admin interface modify the Google Analytics data that is collected in your account. And there is no way back.

Three use cases for Google Analytics filters:

  1. Mobile traffic view: you want to set up a view that only includes mobile traffic. High traffic websites (that don’t use Google Analytics Premium) might want to do this instead of segmenting their data in the reporting interface.
  2. Testing view: you need to test the implementation before it goes live. In order to do that, you want to create a separate view that only includes your IP address.
  3. Target market view: you do business in Finland, Denmark and Sweden. You want to get accurate numbers for your target market so you set up a filter that ensures the data collected only includes traffic from these countries. This will give you the best conversion rate numbers to work with.

These are just a few examples of how powerful filters are if you want to segment your data.

As a general rule I recommend to start with segments. If you find yourself using a segment over and over again, think about creating a separate view with filters.

Google Analytics filters is a very advanced topic. Check out this in-depth guide on filters if you want to learn more about it.

This is it from my side. I hope you have enjoyed reading this article!

What are your key strategies to segment data for greater insights? I am happy to hear your thoughts.

About Paul Koks

Paul Koks

Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including Kissmetrics, SEMRush, Web Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

Google Data Studio 360: How to get Facebook, Bing & Twitter data in 3 minutes

Think Google Data Studio 360 only supports Google Analytics and AdWords? Think twice!

Google recently released a really cool dashboarding tool called Google Data Studio, which lets you easily gather all of your marketing data into one place and build great-looking, interactive dashboards (see for example this web analytics dashboard). It’s a major step forward from the old Google Analytics dashboards, and a game changer for PPC marketers. There’s a free version called Google Data Studio, which lets you create up to five reports, and a paid version called Google Data Studio 360, which is part of the Google Analytics 360 Suite (formerly Google Analytics Premium).

Google Data Studio has built-in connectors to a few Google data sources (Google Analytics, AdWords, YouTube, BigQuery, Attribution 360). Today, expanding PPC campaigns beyond AdWords is mandatory to stay competitive, and most marketers actively use other PPC channels such as Facebook Ads, Bing Ads and Twitter Ads. These non-Google channels are not supported by Data Studio. But no worries, Supermetrics has a solution for you!

Supermetrics empowers Google Data Studio to its full potential. With the Supermetrics Google Sheets add-on, you can easily add many more sources to Google Data Studio, including Bing, Facebook, Twitter, MailChimp, SEMrush, Moz and even Adobe SiteCatalyst. Just follow these steps (also outlined in the video above):

1. Create a new Google Sheet

2. If you don’t have the Supermetrics add-on, install it from the menu bar Add-ons: Get add-ons, or using this link.

3. Launch Supermetrics and run a query for the data you want.

Screen Shot 2016-05-25 at 12.47.23

4. Launch Data Studio

5. Go to DATA SOURCES and click the plus button in the lower-right corner

Screen Shot 2016-05-25 at 12.53.02

6. From connectors, select Google Sheets and the file you just created, click CONNECT

Screen Shot 2016-05-25 at 12.57.05

7. Next, Google shows you a list of fields imported from Google Sheets. Click CREATE REPORT, and in the next window, ADD TO REPORT.

8. You now have a blank report where you can start working with the data. Try adding a table or a chart.

Screen Shot 2016-05-25 at 12.59.59

9. In Google Sheets, you can set the Supermetrics queries to refresh automatically every day, so your Data Studio report will always have the latest data. Go to Add-ons: Supermetrics: Schedule refresh & emailing.

Screen Shot 2016-05-25 at 13.39.37


You can add multiple Google Sheets connectors to the same Data Studio report, to fetch data from different sources or with different metrics & dimensions. 

As you see, Supermetrics and Google Data Studio are a great combo! In the future, we hope to integrate more deeply with Data Studio, so you wouldn’t even need to have Google Sheets in between.

We hope you found this tutorial handy. If so, please tweet it!



How I Save My PPC Reporting Time By 70%

PPC REPORTING· 9-MINUTE READ · By Ana Kostic on May 20 2016



Reporting is a huge time sink for PPC managers. We all try to optimize it and make it as painless as possible. The main problem is despite actual report and data visualization are the key points in our everyday job, report building in most cases is a troubling procedure.

My own goal and motto in regards to reporting is “The time you save building a report, is time you can spend analyzing and solving issues”.

So how did I solve my own PPC reporting problems?

My PPC reporting Journey:

Reporting issues for my case came along with the growth of my client base together with the complexity of channels we were dealing with.

• The first reporting steps

Early in my career, I primarily dealt with Excel reports and templates. In most instances I would export data from Google AdWords, save data files on my computer, and then import them into a client daily dashboard to monitor daily campaign performance.

Apart from this, I had weekly/monthly client reports in Excel, of which the data was imported from data files exported from AdWords.

At this point my report building was very manual. I had to spend a huge amount of time downloading, saving, copying and pasting data.


The daily dashboard took me about 5 minutes to update each morning, and 15 to 20 minutes to set up with each new client. Depending on the complexity of the client, I invested 30 to 60 minutes in building each report. The situation was not ideal, but manageable.

• Growing client complexity, channels and PPC reporting time

The problem emerged when I started to serve a growing number of clients with greater needs, and of course, a greater amount of PPC channels to work with.

Expanding a PPC campaign beyond the AdWords wall in order to be competitive, is mandatory today. It arises from the growing number of channels for each campaign I managed, which led to my PPC reporting nightmare.

My daily dashboard became more difficult to update as I had to export data from 3 to 4 different channels, each with different names, data sets, file formats and exporting processes. This process became so overwhelming that importing all the paid traffic channels into excel was no longer an option.


One ought to know that certain payment methods in Spain do not allow one to have client’s account in one MCC and at that point I had seven different Bing Ads accounts with seven different logins. (yes, seven 😀 ).

My monthly reports were heading the same way, doubling the amount of time needed to build each one of them.

The situation became so bad that some accounts were not even imported into my daily dashboard, which put me into a lot of big drama. I became blind to campaign performance and directed my interests to the data blindness drama, which ate up my time that was supposed to be used to sort out this issue.

Solving the problem

I have a pure marketing background and well developed excel skills as a result of my PPC consulting years. The first thing that would come to anyone’s mind concerning my problem is to use macros, visual basic or any other more tech oriented PPC reporting options. My colleagues, who tried to help me with this, had less time for their own work. It also became a problem as I fully depend on their availability every time I had a reporting issue. Repetitively asking for help and pushing my colleagues also made me uncomfortable.

It was clear to me that I needed some reporting solution which would allow me to integrate all the channels I was using and automate the client’s monthly reports.

Most PPC reporting tools I tried had common problems. They all had rigid reporting templates and interfaces. Some PPC reporting solutions were visually great. Nevertheless, the data had to be organized and represented in a specific way. Another option was missing in almost all these tools was monthly and yearly data comparison.

I had to adapt to a tool and accepted that I could not represent the data in my desired manner. The data I often used for analysis and drawing conclusions was missing. There are powerful data tracking and PPC reporting tools in the market that would allow me to solve these issues. But their prices were out of the question, simply too high for my small agency to afford.


One day I crossed paths with Supermetrics which was familiar to me as an Excel add-on. However, the Excel add-on had a pricing structure of charging for each PPC channel. The sum was higher than what I budgeted for. But thank God, to my rescue came the Supermetrics Google Sheets add-on.

• Before and After

As soon as I started testing the Supermetrics add-on, I realized that it was the solution I was looking for. It became possible for me to build the exact same report I had before in excel, with all my complex tables and data comparison segments. I was able to get all PPC channels that I was working with in one place and in the same place, Google Sheet.


Once all my reports were moved from Excel to Google Sheets, built with Supermetrics add-on, it nowadays takes me just 5 seconds each morning, which the spreadsheet needs to automatically refresh, to update my daily dashboard. Checking whether the formats and charts are okay for my monthly reports takes me around 10 minutes; because Google Sheets charts are not very authentic and need to be double checked. This has reduced my PPC reporting time to a third of what it used to be by having the same reports I had before, refreshed and delivered to my email automatically by Supermetrics.

Thank you Supermetrics 🙂

About Ana Kostic


Ana Kostic is a PPC Expert and Consultant at Bigmomo and a guest writer for Supermetrics. Expert in PPC campaign design and implementation, as well as optimization focused mainly on the return of investment and goal consecution and especializad in international and multilingual campaigns. Passionate about PPC, Online Marketing, Reporting and Data Analysis. You can find her on Twitter or LinkedIn.

10 Reasons Why Digital Marketers Should Love Report Automation

REPORT AUTOMATION · 7-MINUTE READ · By Paul Koks on April 25 2016


Do you spend hours of your time creating reports each and every month? Or do you automate every single piece of it?

A lot of companies still spend too much time manually creating and updating reports.

Report automation is key in a digital world with an abundance of data. It doesn’t matter whether your job directly involves SEO, PCC or digital marketing in general, being efficient with your reporting is something you shouldn’t neglect.

I like to compare Reporting Squirrels with Analytics Ninjas.

Reporting Squirrels

Reporting Squirrels spend 80% of their time in data production activities.

This is often manifested in creation of reports for their direct leader or team. The job includes activities as: pulling data, ad-hoc requests, scheduling reports and dashboards, talking to the IT department to collect more data etc.

Analytics Ninjas

Then we have Analytics Ninjas who spend 80% of their time in analysis that delivers actionable insights.

In service of analysis the job includes: pulling and segmenting data, slicing and dicing, modeling, creating unique datasets and answering relevant business questions. It’s all about actionable insights that drive your ROI of data and analytics!

Who do you want to be?

Let’s dive into the benefits of report automation.

1. It Frees up Valuable Time and Resources

Freeing up valuable time is one of the main benefits of building a fully automized reporting system.

Let’s assume you are employed as a Web Analyst. Every month you spend 20 hours creating, updating and distributing reports.

Imagine what you could do with 20 extra hours:

  • Take a course to further strengthen your analytics skills
  • Write blogposts to share your knowledge and build your brand
  • Educate junior analysts in your organization
  • Come up with thorough advice on how to serve your customers better

You will come up with great ideas that will both benefit you and the organization you are employed!

2. No More Waiting Line

Here is an example from my own experience.

Ten years ago I was spending a lot of time filling in numbers in an Excel sheet for one of my clients, each and every week. Unfortunately it wasn’t automated yet at that time.

This company always liked to get the numbers (new reports) as soon as possible.

You don’t have any problems with this anymore once you automate the creation and distribution of your reports. Your clients or boss can directly access the most important KPIs.

Please be careful to not just send plain reports, but add valuable insights and context to the data as well.

3. Data Accuracy is Usually Higher

Manual intervention leads to errors which can be prevented with reporting automation.

Copy and paste a number at the wrong section and there you go.

Many companies use Google Analytics, Google AdWords and a few other tools. And things can get very complicated. You don’t want to take the risk to mess things up.

This could be the difference between taking the right decision to move your company forward or getting bankrupt.

The more reporting that you do and the more tools you use, the higher the chances are that something goes wrong.

4. Increase of ROI

It doesn’t matter whether you create reports for your own organization or clients.

Freeing up time for other activities than reporting usually helps you to gain more insights from your data.

For example, you have more time to come up with a great hypothesis for A/B testing or to find out how to spend your marketing budget most effectively.

Acting on these insights will greatly lift the ROI of your online business.

Increased ROI

5. Increased Flexibility

Google Analytics standard reports are great to get a first idea on how things are going.

Custom reports are definitely a better option that the standard reports since you can fully customize them to your needs.

However, if you wish to combine data sources, e.g. Google Analytics and Mailchimp, you need to do data manipulation in an external tool.

So if you decide to automate your reporting and use an external tool, you have all the flexibility you need.

In general, you will develop a better overall understanding of your visitors and their behaviour if you combine multiple data sources.

6. Higher Job Satisfaction

Good, loyal analytics employees are scarce. You don’t want them to be tired and bored because of doing “reporting”.

Once a Web Analyst get’s bored because of plain reporting, the job satisfaction drastically declines. And this is not only true for Web Analysts.

In a market with a huge demand, switching jobs is then often unavoidable.

It’s a mutual responsibility to keep the job satisfaction high.

So it doesn’t matter on which side you are. Work on projects that keep everyone motivated!

7. Higher ROI on Your Services

Let’s assume you work at an agency and one of your services is providing your clients with recurring reports and dashboards.

The first setup for a client might take some extra time if you are new to report automation.

The next time you will be much quicker to provide similar or even better results because you know what to!

And very often you can use your last template as a foundation for your new report.

Another thing is that you have a lot of time left for deeper analysis so that you can come up with great insights and advice.

8. Quick Win

Report automation is most often quick and inexpensive to implement.

Of course it all depends on the size and complexity of your current reports. And the knowledge of automation within your organization.

Spending your time to learn how to automate your reporting will pay off big!

Here is what to do you when you have lots of tools and reports in your organization:

  • Start with automating the reports that eat up most of your time
  • Prove to your boss that it saves time
  • Apply the same strategy to the following set of reports
  • Continue until all your reports are automated

Do you think the price is too high?

A full installation of Supermetrics for Google Drive will cost you between € 40 and € 90 a month.

I guess I don’t have to do the math if you spend 10 or maybe even more hours on reporting every month. Your hours are much more valuable and should be spend on generating wisdom instead of plain reporting!

9. Re-Think The Numbers that Matter

Automation takes a lot of time if you have hundreds of reports distributed in an organization.

But is it really necessary? How many people do actually read the reports and act on the data?

Once you decide to automate your reporting efforts, you want to take a critical look at your reports.


Do you have dozens of Google Analytics reports scheduled each and very week? You need to change that..

What are our main KPI’s? What information does my company or client really need?

This decision will make you re-think your numbers and the information you need to provide to your stakeholders.

10. It’s both Fun and Rewarding

You might not agree with me here, but I think report automation is a lots of fun.

It is very rewarding if you have accomplished to automate your reporting process and it simply makes you feel good!

In short, you will want to create a data-driven culture, where you minimize reporting time and focus on the analysis and insights.

There are seven steps the legendary Avinash recommends to follow:


This is it from my side. I hope you have enjoyed reading this article!

Do you already automate your reports? And what are your main challenges? I am happy to hear your thoughts.

About Paul Koks

Paul Koks

Paul Koks is an Analytics Advocate at Online Metrics and a guest writer for Supermetrics. He is a contributor to industry leading blogs including Kissmetrics, SEMRush, Web Analytics World and Online Behavior and the author of Google Analytics Health Check. Paul helps companies to capture valuable insights from simple data. You can find him on Twitter or LinkedIn.

Get more than 90 days of Google Search Console data

Screen Shot 2016-04-08 at 16.32.04

Google Search Console has an annoying limitation of only providing data for the last 90 days. While there’s no way to get around that limitation, we’ve just added a new feature to our system that makes it super simple to get longer time series by automatically stitching together results fetched at different times. With our new feature, when you first run a query, we store the results on our servers, and when you later update the query, the newest results are merged with the existing ones. All this happens automatically in the background, and you don’t need to do anything except turn on this new feature.

This feature is available now in all our reporting tools:

  • If using our Google Drive add-on, check the “Combine new results with old” setting on the Options tab of our add-on sidebar. (For existing queries, you can also type “COMBINE_RESULTS” into Special settings on the SupermetricsQueries sheet.)
  • If using Supermetrics Data Grabber for Excel, after creating a report normally, click “Modify query” and type “COMBINE_RESULTS” into Advanced settings on the querystorage sheet.
  • If using Supermetrics Functions, type “COMBINE_RESULTS” into the settings parameter.

This new setting works with all queries that split by month, week or date. You should set the query date range to last 90 days. Note that old results can only be merged with new ones if the selected accounts, metrics, dimensions and filters remain the same. If those are modified in any way, our system won’t merge the results.

It’s important to note that when this setting is used, your query results are stored for the long term on Supermetrics servers. The results are available only to you, and we don’t make any use of the data other than for your queries. If you stop querying the data using our tools, it will automatically be deleted within six months of the last query.


New Super Pro version with DoubleClick and hourly triggers released

There’s now a new, powerful Super Pro version available for our Google Drive add-on. The new version is targeted to digital marketing agencies and other companies with a major focus on online marketing. While most features will continue to require just the old Pro version, some new features will be only available for Super Pro users. At launch, these include:

  1. New connectors for DoubleClick for Advertisers/DoubleClick Campaign Manager, DoubleClick for Publishers and DoubleClick Search. These new connectors allow both advertisers and publishers to easily fetch their display advertising data into Google Sheets for analysis.
  2. Hourly triggers: Super Pro users will be able to set their Supermetrics queries to automatically refresh each hour, so they always have the newest data available. However, note that Google restricts the processing power of triggers, so we recommend this option only be used with the most important queries, where daily refreshing is not frequent enough.

In the near future, we plan to also add connectors for Adobe SiteCatalyst and DoubleClick Bid Manager to the Super Pro version.

Super Pro is available for purchase here. Current Pro users can upgrade to Super Pro via the Supermetrics account management page (this is linked in the email we sent on purchasing Pro, or can be accessed via Google Sheets menu bar: Add-ons: Supermetrics: Purchasing: Account management).

DoubleClick for Advertisers

Yahoo Gemini added to Supermetrics

Reporting in spreadsheets

The latest addition to our ever-expanding data source list is Yahoo Gemini. This means you can now do reporting on all your search marketing campaigns on Yahoo Gemini as well as on Google AdWords and Bing Ads, and also include your social media campaigns from Facebook (and soon Twitter).

yahoo gemini

Yahoo Gemini is now available in Data source tab of our Google Drive add-on, and in Supermetrics Functions (we may add it to Supermetrics Data Grabber in the future).


Campaign cost data in Google Analytics

We’re best known for our spreadsheet reporting tools, but we also offer something else that every online marketer should use: Supermetrics Uploader, which connects various online advertising platforms with Google Analytics, allowing you to see campaign cost and ROI in GA reports (Google featured Supermetrics Uploader in the Google Analytics Blog earlier this year). Yahoo Gemini has now been added on the list of supported data sources, along with Facebook Ads and Bing Ads (you can also upload CSV formatted cost data from any other ad platform).

Log in here and you can schedule an automatic daily upload with just a few clicks, and after that, you’ll see your Yahoo ad cost & ROAS in GA’s Acquisition: Campaigns: Cost Analysis report and all other reports that include ad cost, as well as in 3rd party reporting tools that plug into to the Google Analytics Reporting API.

yahoo gemini supermetrics uploader



Pricing changes for our Google Drive add-on

Today we’re announcing a new pricing structure for our Google Drive add-on. First some background.

When Google was planning to launch add-ons for Google Drive, they selected us among just a few dozen of companies for early access to add-on development. When add-ons were released in March 2014, we published Supermetrics for Google Drive. It has been a big success, with tens of thousands of users over the world, including lots of digital marketing agencies like iProspect as well as other big names like BBC Worldwide, PBS and Vice News.

For the first eight months, we offered the add-on completely free with all the features. In November last year, we released a paid version, when changes by Google allowed us to add time-based triggers for automatic refreshing and emailing, but we still kept almost everything available for free. We believed the powerful free version would generate enough virality to justify offering it.

Like other SaaS vendors that have terminated or reduced their free offering (see for example Baremetrics or Trakio), we’ve recently concluded that offering so much for free doesn’t really generate enough value to offset the cost. The time we need to put into supporting free users and the server resources they consume is a significant expense, and the viral marketing effect of providing a free version is not large enough to compensate for that. We’ll continue to offer a free version, but it will be less powerful.

Thus we’re now announcing the following changes in the pricing of the add-on:

Paid versions

  • The current Pro version will remain as it is now, price unchanged ($49/month). Pro version users will soon get access to new Twitter Ads and Yahoo Gemini connectors.
  • We’re adding a new Super Pro version priced at $99/month, targeted mainly to digital marketing agencies and other companies that have a major focus on online marketing. Super Pro users will get exclusive access to our new DoubleClick connectors (DFA, DFP, DoubleClick Search). The Super Pro version will be available for purchase in January 2016, and existing Pro version licenses can be transferred over.

Free version & free trial

  • The free 30 day trial with full functionality will remain as it is, so everyone can thoroughly test the add-on to see if it’s worth paying for.
  • After the 30 day trial, the tool can still be used for free, but this free version will be less powerful than before. It can connect to Google Analytics, will be able to fetch max 100 rows per query, and run max 100 queries per day.
  • Current free version users will get to keep the current feature set at no cost until February 15, 2016, and will receive a discount for upgrading to Pro or Super Pro.


New pricing model summary

  Free Pro Super Pro
Data sources
Google Analytics
Google Analytics
Google AdWords
Bing Ads
Google BigQuery
Google Search Console
Facebook Ads
Facebook Insights
Yahoo Gemini
Twitter Ads (coming soon)
Google Analytics
Google AdWords
Bing Ads
Google BigQuery
Google Search Console
Facebook Ads
Facebook Insights
Yahoo Gemini
Twitter Ads (coming soon)
DoubleClick for Advertisers
DoubleClick for Publishers
DoubleClick Search
Simple connectors
Scheduled refresh      
Scheduled emailing      
Try to avoid Google’s sampling setting      
Max rows per query 100 1,000,000 1,000,000
Queries per day 100 (1500)* (10,000)*
Other Restrictions on heavy queries    
$ 49 /month

Buy now

$ 99 /month

Available soon

* You can run more queries than these limits specify, but if you consistently exceed them and your queries are very heavy, we may contact you to negotiate pricing appropriate for your usage level.


This new pricing model will allow us to offer even better service to our paying users and ensures we can develop the product rapidly in the future. On the other hand, we understand the change will be an inconvenience to many free version users. We hope the long transition period (and the discounted paid licenses) will make this easier to manage.

If you have any questions on these changes, don’t hesitate to contact us.




MailChimp connector added to Supermetrics

We’re constantly expanding the data sources available in our tools. Our newest addition is MailChimp, which has been one the most requested APIs among our users. With the MailChimp connector, you can easily fetch email marketing metrics such as email delivery rates, open rates and click rates into Google Sheets and Excel. You’re no longer restricted to MailChimp’s built-in reports but can freely pick which metrics to display and how to split the data, allowing for a much better view of how your campaigns are performing. Getting this data into a spreadsheet is super-valuable, as you can add your calculations and charts, and combine email marketing data with the other data sources we offer.

MailChimp data in Excel

In addition to campaign performance statistics, our MailChimp connector can retrieve data for

  • Automations: performance metrics for automations and individual automation emails
  • Lists: stats like member counts, new subscribers and average open & click rates
  • List members: Email addresses and other details of list members – useful for cross-referencing lists
  • A/B testing
  • Industry stats for benchmarking

MailChimp is now available as a data source in all our reporting tools:



AdWords TrueView video reporting now available in Supermetrics tools

Google’s latest update to the AdWords API provides access to YouTube TrueView video campaigns, and we’ve now updated all our reporting tools to support it. This means TrueView campaign data is now automatically included in all your campaign reporting, and you can also fetch video-specific metrics including:

  • Video impressions
  • Video views & view percentage
  • Percentage and amount of viewers watching 25 %, 50 % , 75 % and 100 % of your video
  • Cost per interaction (for video campaigns, this returns cost per view; for other campaigns, cost per click)

 You can split these metrics by the new video dimensions:

  • Video title, ID & URL
  • Channel ID & URL
  • Video duration

These video dimensions can also be combined with cost and clicks, so you can, for instance, see the cost per click for each of your videos.

AdWords video campaign data is now available in all our reporting tools:

With this update, we’ve also added the engagements and engagement rate metrics, and renamed some fields to match their new names in AdWords (estimated total conversions is now all conversions, estimated cross-device conversions is now just cross-device conversions). We’ve also recently added final URL, campaign start and end dates, bounce rate and advertising channel type (to identify search, display, shopping and video campaigns) to the AdWords field lists.


Supermetrics now connects to Google Search Console (formerly Webmaster Tools)

search consoleWe’re happy to announce our new connector for Google Search Console, after having to remove our old Webmaster Tools connector due to Google changes last spring. The new connector lets you fetch your sites’ organic search data, and it’s even better than the old one, as you can more freely combine dimensions. You can now split the data by both search term and landing page in one query, so you’ll see which keywords bring visitors to each page on your site. In addition to search query and landing page, you can slice the data by country, device and time (though due to Google restrictions, only the last 90 days are available).

Google Search Console is now available as a data source in all our reporting tools:

Note that there’s a small difference in how our tools return data compared to Search Console’s web interface: by default, our tools return all search data (web, image, video), whereas Search Console shows web search only. If you want to get the data for web search in our tools, split or filter by Search type.

We hope you find this new feature useful!

We’ve added Google BigQuery


Our Google Drive add-on now connects to BigQuery, Google’s tool for analyzing large datasets. This is especially useful for Google Analytics Premium users, who can export their raw GA session data into BigQuery, can now easily analyze it using the Supermetrics in Google Sheets. This allows for much more complex analysis than using the Google Analytics API.

To get started, simply choose BigQuery from our add-on’s Data source tab. After logging in, you can select a dataset and start typing SQL. To help you write queries, we display a list of your tables and columns in each table.

If you don’t have it already, you can get our Google Drive add-on here. The BigQuery connector will require the Pro version of the add-on, but everyone can test it for free for now. For Excel users, we offer a BigQuery connector in Supermetrics Functions.

Getting an Excellent Analytics login error?

If you are having problems logging in to Excellent Analytics (invalid username / password), that’s because Google has just shut down the ClientLogin authentication method that EA uses. This means the free Excellent Analytics Excel plugin will now longer work, and the same goes for several other old Google Analytics API tools, such as the getGAdata function by AutomateAnalytics, the predecessor of Supermetrics. If you’re still using any of these tools, you should migrate now to a newer product such as:

Migrating will also give you access to many new, useful features such as avoiding Google Analytics data sampling, multi-channel funnels (MCF) data, automatic charting and PowerPoint generation, multi-profile and multi-segment reports, etc.





Supermetrics Uploader featured on the Google Analytics Blog

We’re very happy to see one of our products, Supermetrics Uploader, featured on the official Google Analytics Blog: Bringing more of your cost data into Google Analytics

Even though less well-known than our other products, Supermetrics Uploader is extremely useful to anyone doing online marketing, as it let’s you get all your marketing data into Google Analytics. If you already track your campaign results in GA (eg. using conversion goals or ecommerce tracking), Supermetrics Uploader combines this data with the campaign cost data, so you can easily see if your campaigns are paying off. Best of all, we’ve made using the product super-easy, so you don’t need to do any advanced configuration to get it running – just select a source ad account and a target Google Analytics web property, and our tool will take care of the rest. You will then be able to see your advertising cost in Google Analytics reports and in all 3rd party reporting tools that plug into the GA reporting API (including our reporting tools).

To get started with Supermetrics Uploader, log in here. A free 30 day trial will begin when you first log in.


Removing spam referral traffic from Google Analytics data

Screen Shot 2015-05-07 at 14.13.14Fake referral traffic from sites such as semalt.com has been increasing lately, which causes serious and growing data quality problems with Google Analytics. One way to combat the issue is using view filters in Google Analytics (see instructions of applying those manually or automatically via the API). While it’s recommended to do this, there are two downsides to this method:

  • It doesn’t work retroactively, so the data already in GA will continue to include the spam.
  • Every time new spam sites appear, you need to update all filters

To address these issues, we’ve just updated all our reporting tools with a setting for removing spam traffic on the reporting side. For example, in our Google Drive add-on, on the Options tab you can find a “Filter out spam referrals” setting. When you use this setting, we filter out all known spam referrals (based on this list gathered by web analytics experts) from your query results. The best thing is, this works retroactively, so fake traffic is cleaned out from all the data you fetch. Also, we can quickly update the list when new spam sites appear, and all changes will be immediately applied to all data, including past queries you refresh.

Using the new setting in our reporting tools:

If you see spam sites that are not being removed by the filter, please contact us so we can update the feature to remove these referrals. We hope you find this new feature useful, and if you do, please share this on Twitter.

SEMrush & Moz data to Google Sheets

SEMrush-Logo      moz-logo

Screen Shot 2015-04-20 at 13.02.43

One of the most common use cases of our reporting tools is search engine marketing and optimization. To make our products even better for this kind of analysis, we’ve now added a SEMrush connector to Supermetrics for Google Drive. With this new integration, you can fetch super-useful data such as:

  • Domains: search rankings, competitors in paid and organic search, ad copies
  • Keywords: organic and paid results, ads, related keywords, keyword difficulty
  • Backlinks: overall list, referring domains and IPs, backlinks by country,
  • Display ads by publisher and advertiser

In combination with the Moz connector we’ve had for a few months, and our other integrations with Google Analytics, AdWords, Bing Ads, etc., you can now bring a lot of useful SEM / SEO data easily into Google Sheets.

To get started with SEMrush reporting in Google Sheets, you just need to input your SEMrush API key to our add-on. If you have a SEMrush license, you can find the API key here. For Moz data, it’s even easier to get started: you don’t need anything, not even a Moz account. In the future, fetching SEMrush and Moz data will require the Pro version of the Supermetrics add-on, but for the time being, it’s not required.

Excellent Analytics and the old GetGAData function will stop working on April 20

When the Google Analytics API was published in 2009, the first solution to get GA data into Excel that was releasesd was Excellent Analytics. Soon thereafter, Supermetrics founder Mikael Thuneberg released a set of VBA functions that also retrieved GA data into Excel: getGAdata, getGAauthenticationToken, getGAprofiles and getGAaccountData. Google detailed these in a blog article in August 2009 (including also solutions released by Tatvic and Shufflepoint) .

The original solutions have been available and working ever since, but now on April 20 2015, Google will shut down the ClientLogin authentication method that these tools rely on. This means the free version of Excellent Analytics as well as the old version of Thuneberg’s functions* will stop working, so if you are still using these, you should start migrating to another solution immediately:

  • For Excellent Analytics users, we recommend Supermetrics Data Grabber, a much more powerful Google Analytics data fetcher that also connects to many other data sources. Formerly known as GA Data Grabber.
  • For users of the old getGAdata function, the easiest migration is to Supermetrics Functions: simply download the new VBA code, attach it to our old workbooks, and instead of using getGAauthenticationToken for authentication, fetch a token from supermetrics.com/functions-login
  • If using Google Drive instead of Excel is an option, you should check out Supermetrics for Google Drive. The free version is very powerful, and in addition, there’s a paid Pro version with even more features.

Migrating all your reporting can be a pain, but the silver lining is that you will then also get access to many useful features like avoiding GA data sampling, multi-channel funnels data, and automatic chart and pivot table creation.

The change will also break GA Data Grabber versions older than 1.38 (released in May 2011). If you have a valid Data Grabber license and are still using a version that old, you can download the newest one here.

*We later used these functions as basis for developing Supermetrics Functions, which will not be affected by the Google changes.

See your Facebook Ads cost & ROI in Google Analytics reports

Supermetrics Uploader is a must-have product for online marketers that love to use Google Analytics reporting: it lets you see your advertising cost in GA reports, so you have the cost and results in the same place. Up to now, Supermetrics Uploader has offered automatic daily transfers from Bing Ads into GA, and the option to manually upload CSV files from any advertising platform. Today, we’re announcing a major new feature: you can now schedule automatic daily uploads from Facebook Ads into Google Analytics.

Getting your ad cost data into Google Analytics offers big benefits. Typically, GA is used to track the results side of your campaigns (goal conversions, ecommerce sales, other onsite behaviour), but the cost side is in another system, the ad platform’s reporting. With Supermetrics Uploader, you’ll get ad cost into the same GA reports where the results are, so you can easily measure the return on your ad spend (ROAS/ROI). If you run campaigns on AdWords, Bing Ads and Facebook Ads, you can have all of these reported in the same place, so you can compare the effectiveness of the different platforms. You’ll also save time, as you don’t need to jump between different reporting systems, but have everything in GA.

We’ve made it super-simple to schedule a daily upload. Just log in at supermetrics.com/uploader and you can set up one in less than two minutes: you only need to choose which Facebook Ads (or Bing Ads) account to use a source, and which Google Analytics web property is the target where the data is uploaded. After that, we upload the latest data every day. You will then see cost and ROAS  in GA’s Cost Analysis reports, and the data will also be available in any 3rd party reporting tools that plug into the Google Analytics API.

We offer a free 30 day trial (no credit card required), and very affordable pricing (starting at $0.89 / account / month) thereafter, if you choose to continue using the product.

We hope you like the new FB Ads connector!

Supermetrics partners with BBC Worldwide to deliver YouTube Content Owner reporting

Today we’re announcing a major improvement in our YouTube reporting capabilities: our tools now include support for YouTube Content Owner (CMS) accounts. This makes it simple for YouTube partners to run reporting on all of their channels and videos, including both content uploaded by the Content Owners themselves and claimed content uploaded by 3rd parties.

These improvements are especially useful to big media companies that need to keep track of engagement and monetization metrics for a large amount of content. One example is BBC Worldwide, which partnered with us to help us add support for CMS accounts. David Boyle, EVP Insight at BBC Worldwide, describes the benefits they get from using our products:

We regularly report on how our brands like Top Gear and Doctor Who are performing on YouTube, Google Analytics and social media. That means we need to regularly run a lot of reports from a lot of different services. This used to take a lot of time and effort, but now we use the Supermetrics tools to automate all of this regular reporting in one report. As a result we have more data and more free time to use that data to drive business decisions. We’re quicker and our brands are smarter as a result.

YouTube Content Owner reporting is now available in all our reporting tools:

We’re happy to say we’re one of the first European companies that have been granted access to the YouTube Content Owner API, and the first business reporting provider to offer these features!



Facebook Ads now available in our tools

fa_gdFacebook Ads has been the top choice for the most needed new data source in all the user surveys we’ve done during the last few years. Facebook restricts access to ads data so it’s taken a while to add it, but we’re happy to announce they have now granted us access, and we have integrated FB Ads into all our reporting tools! This means you can now run reports for all your Facebook campaigns in Google Sheets or Microsoft Excel, taking advantage of all the advanced analysis and visualization features our tools offer. You can also easily combine your Facebook campaign data with metrics from our other data sources like Google Analytics, AdWords and Bing Ads.

Our tools provide access to all the metrics available via the FB Ads API, such as impressions, reach, cost, social reach, and actions/conversions (split by action type to get different types of conversions). Our tools are known for their flexibility, and the FB Ads integration is no exception: you can make any combinations of metrics, split by any dimensions, and filter your data – you’re not restricted to some set of predefined widgets.

To get started on improving your Facebook Ads reporting, get any of our reporting tools:

We hope you like this new integration!



Stripe payments data into Excel & Google Sheets

We recently added Stripe as a payment option on our site and were so happy with their well-designed API that we decided to add Stripe also as a data source to our reporting tools. To our knowledge, there are no other spreadsheet add-ons currently connecting with Stripe, so our integration should be quite handy for any businesses offering Stripe as a payment option and needing more detailed reporting than what Stripe offers on their dashboard.

Like all our intergrations, the Stripe connector gives you the freedom to choose exactly the metrics you want to see and how you want them split. And of course, you can split by different dimensions into both rows and columns, and can add filters to specify exactly what data to fetch. In the example query below, we’re splitting net revenue by product into columns and by month into rows. Once you’ve created queries, you can refresh the data by the press of a button, or in our Google Sheets add-on, schedule automatic refreshing.


Screen Shot 2014-12-01 at 13.39.36



Currently, you can fetch data for charges and refunds. Depending on the reception this integration gets, we may later add customer-centric metrics like churn/retention rates, ARPU and LTV.

Stripe is available as a data source now in Supermetrics for Google Docs, Supermetrics Data Grabber for Excel, and Supermetrics Functions. Let us know if you have any feedback on the integration!


We’ve added scheduled refreshing & emailing to Supermetrics for Google Docs

With Supermetrics for Google Docs, you can build online dashboards combining data from social media, web analytics and online marketing platforms. Unlike other online dashboarding tools in the market, the data processing happens inside Google spreadsheets, so you have complete control over everything: you can fetch exactly the data you want and add your own calculations and charts. With the latest update, we have now made this tool even better by adding the feature that you have most asked for.

Screen Shot 2014-10-21 at 15.52.37
Screen Shot 2014-10-21 at 16.03.18We’re happy to announce that you can now set up triggers that automatically refresh your Supermetrics queries and email the results. This means you can now

  • Ensure your results are always up-to-date by scheduling a daily refresh of queries. You no longer need to open the file and click the refresh button.
  • Share your results by scheduled email, so it’s simple to share with people who don’t use Google Docs.

We’ve put a lot of effort into making it simple to set up triggers. You can do so in just four quick steps:

  1. Click ‘Schedule refresh & emailing’ in the Supermetrics sidebar or the Add-ons menu, to launch the trigger window.
  2. Select the trigger type: daily refresh, or daily/weekly/monthly emailing.
  3. Type a destination email (if it’s an email trigger).
  4. Press ‘Store trigger’

You can also select whether to email all worksheets or just one, whether to email the results as a PDF attachment or as an HTML table in the message body, and you can modify the details of the email message like sender name and the subject. For each file, you can set up multiple triggers. Once you’ve set up a trigger, it will start running every day at around midnight GMT. If your trigger is a weekly or monthly one, it will be processed on the day of week or month you select when setting up the trigger.

Triggers are available now in both the Google Sheets and Google Docs versions of our add-on. We’d love to get your feedback on this and hear if there’s something we can improve!



New visualization options in our Google Sheets add-on

We’ve added a nice new visualization option to Supermetrics for Google Sheets: it can now colour code your results so it’s easier to spot the largest and smallest values. To use the feature, simply go to the Options tab and select a colour format from the “Higlight values with colours” dropdown menu.

Screen Shot 2014-09-05 at 9.10.27


When you run the query, you’ll get something like this: 

Screen Shot 2014-09-04 at 13.26.27


Or this:

Screen Shot 2014-09-05 at 9.14.00


We hope you like this new feature!


Easily duplicate your Google Sheets dashboards for multiple accounts

We’ve added a great new feature to Supermetrics for Google Docs: there’s now an easy interface for duplicating the spreadsheets you’ve built for many accounts. Just select “Duplicate file for another account” from the Add-ons menu or from the Supermetrics sidebar, and follow the instructions displayed. The tool will ask you to pick a new account for each data source that’s being used in the current file. It will then create a new spreadsheet, which is identical to the old one except the Supermetrics queries now fetch data from the new accounts you selected.

This new feature makes your life much easier if you need to create many copies of a report for different clients or departments in your organisation. Just build the report once and duplicate it as many times as you need with just a few clicks!


Screen Shot 2014-08-18 at 16.33.41




Supermetrics at the Google Analytics Partner Summit 2014

The annual Google Analytics Summit for GA Certified Partners and GA Premium users was held in San Francisco this week, and we were happy to be selected as one of only five companies (and the only one outside North America) to get a demo booth for showing our products. We focused mostly on demoing our new Supermetrics for Google Docs add-on, which generated a lot of interest. We received a lot of positive feedback, especially on the Google Webmaster Tools integration, which makes it easy to get the organic search data that’s not provided in GA anymore.

Big thanks to Google for inviting us to the summit and to everyone visiting our booth! For details on all the things Google announced at the summit, see this article.


Supermetrics vs Google Analytics: Add-on feature comparison

In addition to Supermetrics for Google Docs, there’s another Google Sheets add-on that can be used to get data from Google Analytics, the official Google Analytics add-on published by Google. We decided to put together a feature comparison of the add-ons so you can more easily choose between them. Of course, it’s not very objective coming from us, but we’ve tried to to assess the add-ons fairly.

While the table below refers to the new GA add-on, it mostly also applies to the “GA magic script”.


Official Google Analytics add-on
Screen Shot 2014-05-13 at 10.59.13
Supermetrics for Google Docs
Screen Shot 2014-05-13 at 11.04.32

Date range comparisons and multi-segment queries in Supermetrics for Google Docs

We’ve released a new version of our Google Docs add-on with some nice new features:

Automatic comparisons to previous values

Supermetrics for Google Docs can now automatically calculate year-over-year changes and other comparisons. Just go to the Select dates tab and use the Compare to dropdown menu. You can choose to compare to the same date range a year earlier, to the previous date range of the same length, or to a custom period. You can also select the comparison type: change from the comparison period in percent, change in absolute terms, or the value from the comparison period.

Screen Shot 2014-05-12 at 16.16.24 

With this feature, you can easily get data like “top 10 rising traffic sources”. Just set a “Compare to” period, and under Options, set sort by the comparison values. You can use the “# of rows to fetch” setting in the Split by tab to get the top 10 rows, and additionally you can set a filter, for example to get only traffic sources sending at least 50 visits.

Screen Shot 2014-05-13 at 9.02.44

When you run the query you’ll get something like this:

Screen Shot 2014-05-13 at 9.14.07 

Dynamic custom date ranges

Custom date ranges are now much more flexible. Instead of just using the calendar to pick a fixed date range, you can type any date reference accepted by PHP’s strtotime function. Some possible values include:

  • “today”, “yesterday”
  • “first day of this month”, “last day of last month”, “first day of -2 month”
  • “first day of this year”, “first day of last year”
  • “last monday”
  • “-30 days”

When you use relative date reference like the above, the date range is updated every time you refresh the query. You can use these relative date references for both the query date range and the comparison date range. 

Screen Shot 2014-05-13 at 9.21.17


Multiple Google Analytics segments in one query

You can now run queries with more than one GA segment. Simply use the Segment tab to pick several segments and run the query. If you want to see the results separately for each segment, use the Split by tab to split the results by segment name or ID; otherwise the add-on will return the sum of all included segments.

Screen Shot 2014-05-13 at 9.42.37

And you’ll get something like this:

Screen Shot 2014-05-13 at 9.45.10

Automatic refresh and PDF emailing – still waiting for Google to let us do it

Everyone’s asking when it will be possible to schedule automatic query refreshing and emailing of results. We would love to add this functionality and have everything ready on our side, but we need Google to allow add-ons to add time-based triggers. This should be coming at some point soon. If you want to push Google to do this, please add a star to this Google Apps Script feature request.

Get the new version

To get the lastest version of the add-on with the above-mentioned improvements, simply reload the document or spreadsheet and launch Supermetrics from the Add-ons menu. If you don’t see Supermetrics there, you can install the add-on using either of these links:

Get your search query metrics from Google Webmaster Tools

We’ve added a new data source that many users of our tools have been requesting for a long time: Supermetrics Data Grabber and Supermetrics for Google Docs can now connect to Google Webmaster Tools. This data is extremely useful now that Google Analytics shows “not provided” for most search keywords. Things you can get using the new Webmaster Tools reporting include:

  • Search query metrics: impressions, clicks, click-through rate (CTR) and average position. Split by search keyword, landing page, date, week or month.
    Screen Shot 2014-05-05 at 9.12.33
  • Number of URLs on your site indexed by Google, by time
    Screen Shot 2014-05-05 at 9.29.29
  • Number of external links to your site, by domain
    Screen Shot 2014-05-05 at 9.16.34
  • Newest links to your site by date
    Screen Shot 2014-05-05 at 9.25.13
  • Internal links on your site
  • Keywords Google finds on your site

Compared to using the Google Webmaster Tools web reporting, our tools have significant advantages. The main benefits are that you can easily get data from many sites into a single view, you can split the data much more flexibly (for instance, put weeks in rows and pivot search keywords into columns), and you can mix with data from other sources like AdWords and Bing Ads.

Getting started

  • Supermetrics for Google Docs: to start running GWT queries, simply log in to Google Webmaster Tools in the Data source tab. If you haven’t installed the add-on yet, you can do so here.
  • Supermetrics Data Grabber for Excel: download the latest version here, and log in to the Google Webmaster Tools Module. The GWT Module doesn’t require purchasing a separate license, it’s tied to the Google Analytics Module licenses. So if you’ve bought the GA Module, you can start using GWT for no extra cost, just log in with the same Google Account (email address).


The GWT data is not fetched via an official Google API, so this functionality may break if Google makes major changes to Webmaster Tools. We will of course try to keep this working in all situations, but we can’t make any guarantees. This is why we don’t charge anything for the GWT Module, and thus won’t provide any refunds if it stops working due to changes made by Google. Despite not being an official API, the method we use for fetching data from GWT has been endorsed by Google, and we don’t expect it to break any time soon.


New Supermetrics Add-on for Google Docs & Sheets

Google has just launched add-ons for Google Docs and Sheets. We’re proud to be among the first the developers to release add-ons, and we have two of them! You can find and install them via these links:

The Supermetrics add-ons make it simple to fetch all your metrics into Google Docs and Sheets:

  • Connect to Google Analytics, AdWords, Bing Ads, YouTube, Facebook and Twitter 
  • Fetch your metrics into tables and charts
  • Update everything by the press of a button whenever you need the latest figures.

The easy-to-use interface makes it simple to build awesome dashboards and reports, and you can then take advantage of the excellent sharing options in Google Docs to share your results (scheduled PDF emailing will be added soon). 

Get started now! If you need any assistance, visit our support page.



Screen Shot 2014-03-11 at 13.44.38



We’ve added Google Analytics Multi-Channel Funnels

Screen Shot 2014-02-24 at 15.19.39

Both our reporting tools, Supermetrics Data Grabber and Supermetrics Functions, now support Google Analytics Multi-Channel Funnels. This means you can now get detailed analytics on interaction paths leading to conversions on your site, you’re no longer limited to just seeing conversions for the last interaction. You can get a breakdown of conversion value attributed to each channel or channel path. A list of all metrics and dimensions available can be found here.

Google provides the MCF data via a separate API, which means that in many API tools, it’s difficult to combine MCF metrics with other Google Analytics metrics. The MCF API is also limited in providing the data on daily level only. We’ve put a lot of effort into making this as simple as possible for the users of our tools: you don’t need to stich together results from different APIs or convert dates, our tools do this automatically in the background. You can combine MCF metrics into the same reports with other GA metrics, as long as you only pick dimensions that are compatible with both (time, traffic source, AdWords). Our tools also let you split MCF data by month or week.

Supermetrics Data Grabber is by far the most powerful tool for fetching Google Analytics data into Excel, on both Mac and Windows, and now it’s even better with MCF support. To get started, download the latest version here. For existing customers, it’s a free upgrade as always.


Screen Shot 2014-02-24 at 15.04.55



Screen Shot 2014-02-24 at 14.20.41


Introducing the Twitter Module for Supermetrics Data Grabber

We’re happy to announce a new Supermetrics Data Grabber module for accessing Twitter. The Twitter Module is super simple to use: just specify a search keyword, press the Fetch Tweets button, and you’ll get a lists of tweets containing the keyword. As with all Data Grabber modules, you can set up a bunch of reports with different search criteria, and refresh them whenever you want to see the latest results. In addition to the tweet itself, Supermetrics Data Grabber can fetch additional columns such as links to the tweets and the number of times the tweets have been retweeted.

To get started using the Twitter Module, download the latest version of Supermetrics Data Grabber here. A free 14 day trial is activated when you first log in to the module.


Supermetrics Functions can now access Twitter & pivot your data

Today we’re releasing version 2.3 of Supermetrics Functions for Windows Excel and Google Sheets. We’ve heard your feedback and have added several powerful new features:

New getTweets function for searching tweets

In addition to the five data sources we had (Google Analytics, AdWords, Bing Ads, YouTube & Facebook), Supermetrics Functions can now access Twitter to fetch lists of tweets. Just get an authentication token from supermetrics.com/functions-login, paste that to sheet, and specify a keyword for searching tweets. The function will fetch the most recent tweets that match your query. There are many additional parameters you can specify, such as the language of the tweets, and which columns you want to see. The available columns are:

  • TIME Time of tweet
  • TWEET Tweet content
  • LINK Link to tweet
  • TWITTER_NAME User Twitter name
  • NAME User real name
  • LOCATION User location
  • FOLLOWERS User follower count
  • LANGUAGE Tweet language
  • RETWEETS Times the tweet has been retweeted

The Twitter API let’s you make 180 queries in a 15 minute window (if you set max results to more than 100, then each 100 results will count as one query). If you exceed this limit, the function will wait until the next 15 minute window starts. Thus if you run a large number of queries in a short time, data fetching will slow down.

GetData function is now Supermetrics

In the new version, we’ve added a new data feching function called Supermetrics. So now instead of typing “=getData(…”, you can use “=Supermetrics(…”. We decided to create a new function because we’re adding some new parameters (more on these below) and removing old ones, and we also wanted to rearrange the parameter order. The new version is still fully backward-compatible, so you can add the new code to your existing reports that use getData or getGAdata, and everything will work as before. The parameters for the new function are Supermetrics(token, profileID, metrics, startDate, endDate, dimensions, pivotDimensions, filters, segment, sort, settings, maxResults, maxCategories). You can find further information on the parameters here

Supermetrics Functions can now automatically create pivot tables of your data

We’re adding a super-powerful new feature, a pivotDimensions parameter that you can use to get pivot tables of your data. You can use this in combination with the dimensions parameter to split your data both into rows and columns. This makes it much easier to do many kinds of analyses that would have previously require using lookup functions to pivot the data, like plotting the developments of several items over time as in the attached example. The new maxCategories parameter can be used to control how many columns will be fetched.

Even using the older version of the functions, you can immediately start using the pivoting feature by suffixing any dimension name with “_pivot”. For example, to split by year and month and pivot by medium, type “yearmonth&medium_pivot”.

Use the new settings parameter to customize your query

In the new version, we’ve removed the old includeHeaders and includeDimensionColumns parameters and replaced these with a new settings parameter, which can be used to control many aspects of the query. Below is a list of currently available values for this new parameter, you can use multiple values by combining with commas:

  • SAMPLING_NOTE displays whether Google has sampled the results (only relevant for Google Analytics queries)
  • AVOID_SAMPLING tries to avoid Google’s sampling, will slow down data fetching significantly so should be used sparingly (only relevant for Google Analytics queries)
  • NO_DIMENSIONS splits by the specified dimensions but doesn’t display them (replaces the old includeDimensionColumns parameter)
  • COMBINE_DIMENSIONS concatenates dimension values when multiple dimensions have been specified
  • SUM_ALL when specifying multiple profile/account IDs, this setting will sum all results together
  • INCLUDE_HEADERS will include headers in the data (replaces the old includeHeaders parameter)
  • NO_HEADERS won’t include headers in the data (replaces the old includeHeaders parameter)

More reliable data feching in Google Sheets

Supermetrics Functions version 2.3 for Google Sheets contains several improvements which will make data fetching much more reliable. However, due to the limitations of Google Sheets, you may still encounter errors when running a large number of queries in a short time.

Get Started Now

To get started using the new version, see the Getting Started section here. Like always, if you have a license for Supermetrics Functions, this is a free upgrade (see instructions for upgrading your existing workbooks). However, if you want to use the new getTweets function, you will need to buy a license for Twitter (you can of course test it for free first).

We’re now Supermetrics


This week marks a major milestone for our company: we are retiring our old AutomateAnalytics, GA Data Grabber and GA Data Uploader brands to become Supermetrics. We’re doing this because we want to bring our various tools closer together and to make it clearer what we are offering. After reviewing hundreds of names, we decided on Supermetrics, a name we think is memorable, perfectly describes our superb products, and is a bit fun without being silly. We hope you like the new name and visual style!

We are renaming our tools as follows:

  • GA Data Grabber -> Supermetrics Data Grabber: Easy-to-use report automation tool for Google Analytics, AdWords, Bing Ads, YouTube & Facebook
  • GA Data Uploader -> Supermetrics Uploader: Simple tool to upload ad cost data into Google Analytics
  • AutomateAnalytics Functions -> Supermetrics Functions: Most flexible solution for intergrating Google Analytics & other APIs with Excel & Google Sheets, targeted to advanced spreadsheet users

We’re continuing the AutomateAnalytics blog as Supermetrics Blog.

Connected to the name change, we have also completely redone the look of Supermetrics Data Grabber, to make it both nicer to look at and easier to use. The latest version also includes all the AdSense metrics Google recently made available via the Google Analytics API, so you can now run reports detailing the ad revenue for each page on your sites. If you haven’t already, give it a try now!


Easy AdWords reporting in Google Spreadsheet

UPDATE March 2014: We’ve published a new Google Docs add-on that makes it even easier to get your metrics from AdWords and other sources: Supermetrics for Google Docs

Our AutomateAnalytics Functions provide a great way of building AdWords reports in Google Spreadsheets. The functions can be typed to spreadsheet cells, and using the function parameters, you can get all kinds of data available in AdWords. This allows you to create a Google Spreadsheet dashboards with exactly the data you want. You can then take advantage of all of Google Spreadsheet’s formatting and sharing features to use the spreadsheets for either internal analysis or client reporting. If you’re also using Bing Ads, you can add Bing CPC data into the same reports (the functions can also fetch data from Google Analytics and YouTube, and soon from Facebook Insights and Flickr).

To illustrate what you can do with these functions, we’ve created a new AdWords reporting spreadsheet that you can find here. Open the sheet, fetch an authentication token from analyticsfunctions.com and paste it to the sheet. It will then automatically fetch your data into the reports. We’ve configured five reports:

  • Monthly metrics: your main metrics per month for each campaign and ad group. You can define how many years of data to fetch
  • Top ad groups
  • Top ads
  • Top keywords
  • Keyword vs. matched search query combinations
Using the instructions here you can add your own queries to fetch any AdWords data listed in this document. With AutomateAnalytics Functions, you can easily create completely customized CPC reports, add advanced calculations and visualizations, and join with data from other sources. You’re no longer limited to the built-in reporting options of AdWords or to inflexible (and much more expensive) 3rd party reporting tools like Raven Tools.

GA Data Grabber can now avoid Google Analytics data sampling

When using the Google Analytics API to fetch data for sites with high traffic volume, Google often returns sampled results. These usually differ from the figures displayed in the Google Analytics web interface by a few percent. Data sampling is especially likely to occur when fetching data over a long date range, splitting by several dimensions, or using advanced segments to filter the results.

The benefit of Google’s data sampling is that you usually get the results really fast, and with high enough accuracy. But in some cases, you may prefer to let the query run longer to get the exact figures. Due to the feedback we’ve received from GA Data Grabber users, we have added some new functionality to the tool to accomplish this: GA Data Grabber can now avoid Google’s data sampling in most cases (sampling may still occur when fetching large result sets). To use the new feature, just check the “Try to avoid Google’s data sampling” option on the Analytics tab (the setting is off by default, as in most cases it makes sense to let Google sample the data). Note that when using this option, depending on the report configuration, it may take several minutes to get the results.

This new feature is available in GA Data Grabber version 1.68, which can be downloaded here

In this update we’ve also added:

  • Two new content expirements dimensions to the Analytics Module Split by dropdown menus 
  • The ability to fetch unique visitors (and other unique count metrics) split by Monday to Sunday week
  • Optimizations that make data fetching even faster

New report types available in GA Data Grabber

Producing great-looking reports automatically is one of the big benefits of using GA Data Grabber: you don’t need to spend time formatting the data and creating charts, as GADG does all this for you. Still, we’ve noticed that in addition to the built-in GADG report formats, many people also build their own dashboards and visualizations that use the GA Data Grabber reports as data source. To make this easier, we’re releasing a new report type in GA Data Grabber: unformatted raw data reports. These contain the data in a simple, unformatted table that can be used as a source for dashboards, pivot tables, charts etc. See screenshots below of a raw data report and a regular formatted report.


Raw data report
Formatted report
We’ve also added the option to run “summed” reports. If you select more than one Google Analytics profile/AdWords account/Bing Ads account/YouTube video to the report, GA Data Grabber will ask whether you prefer to see stats for each of them separetely or all summed up. This new feature makes it easy to run reports that sum metrics from many sites.
Report type selection

Both of these new features are available in the newest GA Data Grabber version in Google Analytics, AdWords, Bing Ads and YouTube reports (they are not yet available in Facebook reports), and work in both Windows and Mac Excel. You can get the latest version here.

Upload cost data from any source into Google Analytics

We’re happy to announce a new feature in GA Data Uploader: you can now use it to upload CSV files containing ad cost data into Google Analytics. This lets you get cost data from any source, for example Facebook Ads, LinkedIn Ads or Yahoo, into GA.

GA Data Uploader automatically guesses which CSV columns contain
 what data, and converts the file to the format Google accepts
We’ve made the tool super simple to use. There are two important features that set GA Data Uploader apart from other similar tools, and make it much faster and easier to run uploads:
  1. GA Data Uploader does not require that the CSV files conform to a specific format. Just upload any CSV (or TSV), and GADU automatically converts it to the format that is accepted by Google. This can save you a huge amount of time, as you don’t need to manually tinker with the file to get it into the correct format.
  2. When using GA Data Uploader, each CSV file you upload can contain data for multiple dates. The only limit is the max file size of 2 MB. Other tools require that you split the data to separate files each containing just a single day’s data, which can mean a lot of work.

After Google has processed your file, the cost data will be visible in Google Analytics in the Traffic Sources: Cost Analysis report. The big benefit you get from this is, of course, that you can then see the ROI of your campaigns directly in GA, as GA can calculate this based on the advertising cost and ecommerce revenue metrics.
GA Data Uploader lets you upload up to 5 files for free. Additional uploads are available for $0.99 per file. In addition to CSV uploads, you can use GA Data Uploader to schedule an automatic daily upload from Bing Ads into Google Analytics.
Get started using GA Data Uploader here

Introducing the YouTube Module for GA Data Grabber

When we ask GA Data Grabber users which new data source they’d most like to see added to the tool, YouTube has consistently been one of the top answers. We’ve heard your wishes and have now added a YouTube Module. This new module lets you fetch statistics for any number of YouTube channels and videos into one report, so you can easily monitor all your YouTube activity. As with all GA Data Grabber modules, reports can be created very flexibly: you can freely choose which metrics to include, and how to split the data. Metrics you can get include:
  • Video views
  • Unique viewers
  • Time viewed
  • Average % of video viewed
  • Subscriptions to your channel
  • Likes
  • Favorites
  • Shares

You can get the total figures, or split by time, country, gender, age, traffic source, or playback location. Compared to using YouTube Analytics, GA Data Grabber offers many benefits, mainly:
  • Getting metrics for many channels in one place
  • Seeing the developments for many videos simultaneously
  • Automatic calculation of how the metrics have changed compared to the previous period of same length, or the same period a year earlier
  • Combining the data with other data sources available in GA Data Grabber, such as your site statistics from Google Analytics and your Facebook page metrics
  • Having all the data in Excel, where you can add your own charts and calculations
  • One-click PowerPoint report creation

As with all GA Data Grabber modules, the YouTube Module has a free 14 day trial with full functionality. You can get it here. In addition to GA Data Grabber, you can also fetch YouTube data into Excel and Google Docs using our AutomateAnalytics Functions.

Total video views and time watched

Channel totals: video views and average time watched by month

Views by month for multiple videos in one report

AutomateAnalytics Functions can now fetch AdWords & YouTube data into Excel & Google Spreadsheet

Last summer we published a new version of our Google Analytics VBA functions, when the old 2009 version was broken by changes Google did to their API. We’re now releasing the first major update to this, with two major changes:
  • In addition to Excel, the functions now work in Google Docs. The usage is just the same in GD as it is in Excel. To get started, get the template spreadsheet here (you need to be logged into a Google Account for the link to work). You can transfer dashboards created in Excel into Google Docs following the instructions here.
  • In addition to Google Analytics, the functions can now fetch data from AdWords and YouTube (the latter is still in beta). There are tabs for these new data sources in the Excel and Google Docs template spreadsheets.

We hope you like these changes! We’re going to add more data sources in the coming months, starting with Bing Ads and Facebook Insights. And very soon, we’re going to add the YouTube capability to our flagship GA Data Grabber tool.
For more information on this tool, see here.

Get your Bing Ads cost data into Google Analytics

At the Google Analytics Conference in October, Google published a new cost import API, which allows importing cost data into Google Analytics. This API has now been rolled out to all GA users, so we’re ready to introduce our new tool, GA Data Uploader, which uses the new API to link your Bing Ads accounts with GA.
Our aim with GA Data Uploader was to create a tool that makes it as simple as possible to use the new API, without needing to worry about any of the technical details. With our tool, it won’t make more than 5 minutes to get your automatic daily upload running! The only steps you need to take are:
  • Log into Google Analytics & Bing Ads
  • Pick which Bing Ads account is the data source
  • Pick which Google Analytics web property is the target
  • Add a custom data source into the GA web property, if you haven’t added one yet
  • Press “Schedule uploads”
After you’ve scheduled the upload, it runs automatically every day, and you can see your Bing Ads cost data in GA’s Traffic Sources: Cost Analysis report:

The data can also be accessed with Google Analytics custom reports, as well as any reporting tools that use the Google Analytics API, such as our GA Data Grabber

Having Bing Ads cost data in GA brings two big benefits:
  • You can measure Bing Ads ROI: compare ad cost with GA’s ecommerce and goal conversion metrics
  • You can see all cpc data in one place, no need to log into Bing to check how the campaigns are doing

GA Data Grabber at the Google Analytics Conference

We were really happy to be one of only five tool vendors that Google invited to have a booth at the Google Analytics Conference held last week in Mountain View, California. The conference was attended by 400 Google Analytics Certified Partners and Google Analytics Premium clients from over the world.
Lots of great new stuff were announced by Google, including the cost import API, which allows you to import cost data from other data sources into Google Analytics. We received early access to this new API and for the conference, we released a new tool, GA Data Uploader, which uses this new API to import Bing Ads data into GA. In our booth, we did of course also display GA Data Grabber, the #1 reporting tool for GA. Both tools got a lot of attention from conference attendees, and we’re sure we will be getting many new customers soon! It was also great meeting many of our existing customers in person for the first time.
Some photos from our booth:

Lots of new data available via the Analytics API

Google has just published an update of the Google Analytics API, which adds lots of new data fields, including detailed information on mobile devices and social interactions. We’ve included the new data in version 1.64 of GA Data Grabber, which is now available for download. Users of our Google Analytics VBA Functions can also start using these new fields immediately, simply by typing the field names as function parameters. A full list of available metrics and dimensions can be found here.
GA Data Grabber report on mobile devices:

GA Data Grabber report on social actions:

Multi-segment reports in GA Data Grabber: branded vs non-branded keywords

We’ve just uploaded version 1.63 of GA Data Grabber, with a great new feature: the ability to pick several Google Analytics segments into one report. This opens up the possibility to do all kinds of analyses that would’ve previously required running several reports and combining the results. One useful example is comparing branded vs. non-branded search keywords. Just create these segments in Analytics, and they will be visible in GA Data Grabber’s segment list. You can then pick them into a report, for example splitting by month to see the developments on a monthly level:

Of course, this is just one example, and there are many other useful reports you can now run. You can get the new version here. As always, the upgrade is free for everyone having a valid GA Data Grabber license.

Google Analytics VBA Functions for Excel – new version available

UPDATE: Now also available for Google Docs, see more information here

One of the most popular solutions for fetching Google Analytics data into Excel has been my set of VBA functions that can be used on an Excel worksheet just like any of Excel’s built-in functions. Shortly after the Analytics API was released three years ago, Google mentioned it as the #1 way for accessing the API from Excel. There are several other tools for fetching Analytics data into Excel (such as our GA Data Grabber and FasterMetrics tools), but nothing can match the flexibility of the VBA functions.

Now after three years, due to changes Google has made to the Analytics API, the original functions have become nearly unusable, and will break completely when the ClientLogin authentication method is removed. As many companies rely on the functions for their reporting, we have decided to publish a new version that works with the new Analytics API.

The new version of the Google Analytics VBA functions for Excel can be downloaded here. From a user perspective, we have kept the new version as close to possible to the old one, to make it easy to migrate existing reports. The functions have the same names (getGAdata, getGAaccountData), and accept the same parameters. This means you can simply copy the new VBA code from the file linked above into your old report files. 

There are some changes though, the biggest being that instead of the getGAauthenticationToken function, you need to visit analyticsvba.com to get an authentication token. These tokens will not expire like the old ones, so you only need to do this once. With this new OAuth authentication method, you don’t need to enter your Google account password to the Excel sheet, which makes this much better from a security point of view. The token you place on the sheet only gives access to Google Analytics data, not other parts of your Google Account, and it can be revoked at any time from your Google dashboard.

There are some other improvements as well:

  • You can fetch data for multiple profiles with a single query, just combine the profiles IDs with an ampersand (&). This is much faster than the old way of typing a separate getGAdata query for each profile.
  • You can fetch an unlimited number for metrics in a single query
  • You can fetch more than 10000 results with a single query, using the new maxResults parameter
  • You can specify that the dimension values are not shown in the results using the new includeDimensionColumns parameter (this is handy, for example, if you want to fetch data on monthly level for multiple segments side by side, and don’t want each query to return the month numbers)
  • The authentication token will not expire, unless you choose to revoke it (with the old version, the tokens expired after 30 days)

To justify the development and maintenance work required for this new version, it comes with a small annual price of € 99. You get a free trial at first, and if you want to continue using the functions, you can make the payment at analyticsvba.com. What you get for this price is a reliable solution that we will guarantee to keep working despite changes Google makes to the API, and support through our help forum.

If you are new to the functions, to get started take a look at this tutorial. You can find a reference for all the function parameters here. The functions work in Windows Excel 2003 and later. For Mac users, we offer GA Data Grabber and FasterMetrics.

Let us know if you have any feedback of the new version!


Check out our new excellent analytics tool, now in beta

We’re happy to introduce our new Google Analytics tool for Excel users, FasterMetrics. It’s an easy-to-use plugin that gets your Google Analytics data into Excel, and works on both Mac and Windows Excel. It’s similar to a tool called Excellent Analytics, but it also works in Mac OS X, is faster, and lets you set all your query parameters dynamically using Excel functions – this makes it possible to automate complex reporting dashboards. Compared to GA Data Grabber, FasterMetrics has more limited functionality, as it lacks some features like automatic data visualization and exporting to PowerPoint, but for some purposes, a simple tool like this can be more convenient.

FasterMetrics is currently in beta: you can download the beta version here. After opening the file, on Windows Excel 2007/2010 you will see the button to launch it in the Add-ins tab. In Mac Excel 2011, you will see a custom toolbar pop up.

You can use the full version FasterMetrics for 30 days for free. After that, you can choose to pay for the full version, or continue to use the tool for free, with limited functionality.

We’re still developing the tool, with the aim to get it out of beta in August. If you have any feature suggestions or problems with the tool, please post these to our help forum. Thanks.

Google Analytics Account Overview report with GA Data Grabber

The old Google Analytics interface is being deprecated, and even though the new one is in many ways an improvement, it lack some features of the old interface. One of these is the Account Overview, which displays on one page certain core metrics for all of the profiles of an Analytics account, and also shows how these have changed from the previous period of the same length. Luckily, with GA Data Grabber it’s very simple to make a report with the same information – just watch the video below to see:

Account Overview in the old Google Analytics interface:

Account overview report in GA Data Grabber:

Get GA Data Grabber here

GA Data Grabber featured in the Google Analytics Blog

The official Google Analytics blog has a new article out that shows how useful GA Data Grabber can be for automating multi-site Google Analytics reporting. The American TV network PBS is featured as a case study. Check out the article here.

Lots of thanks to Amy Sample from PBS for agreeing to the case study, and to the Google Analytics API team for releasing the article!

New Facebook page & app analytics tool now available

We’re happy to announce a new Facebook Module for GA Data Grabber, the #1 reporting tool for Google Analytics, AdWords & MS adCenter! The Facebook Module makes it easy to keep track of a large number of fan pages and applications, as it can fetch the numbers for dozens of pages/apps into an Excel sheet in a matter of seconds. But it’s not just a data fetching tool, it also visualizes the data, automatically calculates comparisons to previous year figures, creates PowerPoint reports by the push of a button, and much more.

More information of GA Data Grabber & free trial download can be found here. Information specifically on the Facebook Module can be found here.

Check out the video and screenshots below:

Get the beta of the new GA Data Grabber

Update: the new version has been released and can now be downloaded from http://supermetrics.com/product/supermetrics-data-grabber/

We’ve been working on a big update to GA Data Grabber. We’re now at the beta stage – you can download the beta version here.

I’ll write a more detailed post on the new features once this version comes out of beta, but some main feature included:

  • A new Facebook module: gets the metrics for your Facebook fan pages and applications into Excel, making it easy to analyze. You’ll get many metrics not available elsewhere.
  • Much easier filtering
  • Exporting reports to a separate Excel file
  • Option to use a template with the PowerPoint export feature
  • Improvements to the automatically created charts
There are many other changes too. But there may be some bugs left too – if you notice any, please let us know (info@supermetrics.com). Of course, other feedback on the new features, and especially the Facebook module, is also welcome.

More information on GA Data Grabber can be found here.

We hope you enjoy the new version!

Translation Tool for Excel

Two years ago, I published a small script I made for using Google Translate in Excel (http://supermetrics.com/2009/09/excel-function-for-translating-text.html). I didn’t give it much attention since, but apparently it’s grown quite popular. Unfortunately, Google is now shutting down the free translation API that my script used, so it will stop functioning very soon. Many people contacted me regarding the issue, so I decided to make a new Excel tool for the new, paid Google Translate API. 

This new tool is now available here.

The new tool is not completely free, but the usage cost is very low. It’s also much faster (up to 40 times) than the old solution, can translate much longer phrases, and is more reliable. There’s a free trial, so you can fully test the tool before buying. This tool is very simple to use, just select a cell range and the language you want to translate it to, press a button and the tool will conduct the translation in matter of seconds.

Warning: I’ve noticed someone is selling a tool called “Google Translate for Excel”. This is not my tool; it looks like someone’s just copied my earlier free script (which will stop functioning very soon), and put a price tag on it.


New version of the AdWords Addin for Excel

We’ve just uploaded a new version of the AdWords Addin for Excel. This new version uses the new AdWords API version, which means you don’t need to pay by usage anymore – the only cost is the annual license price (currently $199 USD per MCC). When using the functions, you no longer input an AdWords developer token as a parameter.

We’ve also simplified usage so that you no longer need to select a report type. Just select which fields you wish to fetch, and the tool will automatically determine the optimal report type in the background. The field names are also no longer case-sensitive. All this makes usage of the tool much easier.

Download a demo worksheet here. (Type your AdWords login credentials and the tool will automatically fetch some data for you. You can see how the functions are used and modify the parameters, and add new instances of the functions)

For more information and pricing, visit http://analyticsfunctions.supermetrics.com/

(Using this tool requires learning some basics of array function usage in Excel. For an easier tool, you should check out GA Data Grabber)

Usage of GA Data Grabber AdWords module is now free!

Google has published a new version of the AdWords API: with this new version, it’s no longer necessary to purchase AdWords API units in order to run reports. We have just uploaded a new version of GA Data Grabber that takes advantage of the new API version, you can get it here. This means that from now on, the only expense of using the AdWords module is the small annual GA Data Grabber license fee (currently at $199) – no extra fee for running reports anymore! If you haven’t bought a license yet, testing the AdWords module is now also much easier, as you can run as many reports as you wish during the 7 day trial period.

The old API version will be shut down at the end of February 2012. As the update includes some major changes to reporting, all existing users of GA Data Grabber AdWords module must upgrade to a newer GADG version before that date in order to be able to run new reports.

Note that using the GA Data Grabber Keyword Tool (included in the price of the AdWords module) still requires buying API units.

This update makes using GA Data Grabber as an AdWords reporting & analysis tool much more convenient, as there’s no more uncertainty related to the usage cost of the tool. In addition to this, we also wanted to improve the user experience of the AdWords module. In the latest version of GADG, you no longer need to select an AdWords report type when creating a report –  GADG now does the selection automatically in the background. Tbis makes creating report much easier, as you no longer need to look through different report types to find which of them include the field combination you wish to include in your report. We’ve also updated the list of available report fields to match the new API version.

Download the latest version of GA Data Grabber with these improvements here.

New Microsoft AdCenter reporting tool

After the transition of Yahoo Search Marketing to Microsoft AdCenter (formerly known as MSN AdCenter) last year, AdCenter now serves ads to both Bing and Yahoo search engines, and currently has around 30 % of the US market. To help advertisers working with AdCenter, we are now introducing a new tool, GA Data Grabber AdCenter Module, which makes it easy to see how your ad campaigns are doing. 

To test for yourself, download GA Data Grabber and log into the AdCenter module.

The simple interface of the tools makes it easy to run reports, but it’s also very flexible, allowing to conduct analyses not possible via the AdCenter web interface. You can freely specify which metrics to include in a report and how to split them (for example, by time, by campaign, ad, keyword etc). Running reports for many campaigns is very fast, and you can easily duplicate reports for multiple accounts, if you are managing more than one. GA Data Grabber automatically creates charts out of the results, and you can export them to PowerPoint by the press of a button. GA Data Grabber works in MS Excel, making it easy to modify the reports and do additional calculations with the data.

GA Data Grabber is a huge time saver for anyone working with search engine marketing. The very low annual cost is easily outweighed by the time you save when using this tool to track campaign performance. And there’s a free trial with full functionality, so you can test that this is true before buying.

Screenshots: report builder interface; report with campaign data on date level. Click to enlarge.

In addition to Microsoft AdCenter, GA Data Grabber can access Google Analytics and AdWords data. Click here for more information on GA Data Grabber. We’re also marketing the AdCenter module separately as AdCenter Data Grabber.

If you’re working with AdCenter, give GA Data Grabber a try straight away!

8 new metrics available in GA Data Grabber

We’re happy to announce the addition of 8 new metrics into GA Data Grabber! Google hasn’t updated their API, but GA Data Grabber now uses existing dimension fields to calculate new interesting metrics, which are not available via the Analytics web interface nor through other tools that use the Analytics API. The new metrics are listed below. To start testing immediately, get the latest version from http://supermetrics.com/.

Ecommerce, 2 new metrics:
  • Average number of days to transaction: how many days from the first visit does it on average take for a visitor to purchase? The bigger the average is, the more days the visitors take before making the purchase. The day of the first visit is counted as zero; if the average is zero, this means all transactions are done immediately on the day the visitor first arrives on the site.
    The Google Analytics web interface does provide a simple distribution for this (in the new GA interface: Conversions -> E-commerce -> Time to purchase), but it doesn’t show how this develops over time, or relative to other factors such as marketing campaigns. See for example the attached screenshot of a report showing the development of this metric by month and by traffic source – changes on the site and in campaign emails can have a significant effect on how fast visitors are converted to buyers.
  • Average number of visit to transaction: same as above, but counts how many visits it on average takes for a visitor to purchase.

SEO, 3 new metrics
  • # of referring domains with visits: shows how many different domains are sending traffic to your site. Great metric for assessing link-building efforts. Attached example screenshot shows how the number of domains linking to AutomateAnalytics.com has developed over the last two years.
  • # of keywords with visits: displays how many different keywords are sending traffic to your site. When plotted over time, this can be used to evaluate the success of search engine optimization. Note that to exclude PPC keywords from reports with this metric, you can use the advanced segment “Non-paid Search Traffic”, or a filter string: medium==organic
  • # of landing pages with entrances: measures how many different pages draw visitors to the site. Query strings (starting with “?”) and fragment identifiers (starting with “#”) are stripped from the URLs before counting how many unique landing page addresses are found.

Content, 1 new metric:
  • # of pages with pageviews: how many different pages have been visited on the site? This metric can be used to evaluate how much different content is being viewed and how this develops over time. Each unique URL that has received pageviews is counted, but query strings (starting with “?”) and fragment identifiers (starting with “#”) are automatically stripped.

Location, 2 new metrics:
  • # of countries with visits: from how many countries has the site received visits? Can be used to evaluate the geographical spread of traffic.
  • # of cities with visits: same as above, but counts cities.

These are all included in the latest version of GA Data Grabber. You can download it here: http://supermetrics.com/

These new metrics open up many new opportunities for using GA Data Grabber. We hope you find them useful.

GA Data Grabber now groups site content by directory

One popular report of Google Analytics is Content Drilldown, which lets you see the metrics per content on different directory levels, instead of by individual URL. This report isn’t available through the Analytics API directly, but we have now managed to add it into GA Data Grabber, by parsing it from the available data. There are four new dimensions available in GA Data Grabber: page directory levels 1 to 4 (you’ll find these in the “Split by” dropdown menus under “Content”). These dimensions range from a more general to more detailed categorization of your content. For instance, for the URL “http://supermetrics.com/2011/03/google-analytics-adwords-tool-for-mac.html”, the values for these dimensions would be:

Page directory level 1:  /2011/
Page directory level 2:  /2011/03/
Page directory level 3:  /2011/03/google-analytics-adwords-tool-for-mac.html
Page directory level 4:  /2011/03/google-analytics-adwords-tool-for-mac.html

If the URL has less directory levels than specified in the dimension, then GA Data Grabber will return the full URL, but query strings (starting with “?”) and fragment identifiers (starting with “#”) are automatically stripped. You can of course still also access the complete URL by using the Page path dimension.

The new dimensions make it easy and fast to get a view of how the different site sections are performing. For example, take a look at this screenshot of a report that plots pageviews for directory level 1 by week:

To get your hands on the new features, go download the latest version of GA Data Grabber. There’s a free 7 day trial, and with the annual price for the full version at just $139, you’d be crazy not buy it!

New free Analytics tool available: metrics by hour of day

UPDATE: Due to changes by Google, this tool no longer works. Instead, you should check out the AutomateAnalytics Functions, which you can use to create a report similar to this, and countless others – it’s the most flexible way of getting Google Analytics and AdWords data into Excel and Google Spreadsheet.
It’s been some time since I’ve last released anything free of charge, but now’s the time! By following this link, you can download an Excel tool which fetches Google Analytics metrics by hour of day, and splits that by day of week and by date. Once logged in, you can pick any of your Analytics profiles, and filter the results by an advanced segment. You can freely set a date range, and pick one of many metrics.

This works using my Analytics VBA functions, is completely free to use and does not require installing a plugin! The only thing it requires is that you enable macros in Excel’s security settings (see instructions). (Currently works on Windows only – if someone’s interested in contributing to the development cost, I can adapt it to Mac Excel too.)
The inspiration for this comes from an episode of Google’s Web Analytics TV, where someone asked if it’s possible to create a report like this, and was pointed to use a paid solution, which requires a plugin installation. In general, any dashboards like these can easily be created using my VBA functions for free with a few minutes of work (though it did take me almost an hour and half to build this one, since I wanted to add a nice interface too). It’s even easier with our GA Data Grabber tool, which you can use to quickly create any of these reports, and which is not restricted to a predefined set of dashboards.

Automate Snoobi reporting in Excel

Today we’re happy to announce a new product, Snoobi for Excel. It’s an analysis tool working in MS Excel that automatically fetches and visualizes your Snoobi data. Snoobi for Excel creates in a matter of seconds reports that would take hours to set up manually. With this tool, you can put your time into interpreting the numbers rather than waste it on manual copy-paste work. It even automatically puts together PowerPoint presentations of your reports. To read more and to download a free trial, visit SnoobiForExcel.com.
For those who’ve never heard of Snoobi, it’s a popular web analytics tool in many parts of Europe. (Note that Snoobi is a whole separate web analytics tool and not connected to Google Analytics. For GA users, we recommend GA Data Grabber.)

GA Data Grabber now supports multiple logins and OAuth

We have recently added several major new features to GA Data Grabber. Here’s a brief overview of the most important ones. To test them for yourself, download the latest version here.

Support for multiple Analytics logins

GA Data Grabber now lets you log in with multiple Analytics users (Google Accounts) simultaneously. This is a handy feature if you don’t have a single user account that has access to all the Analytics accounts you need to follow, for example, if you have a separate user account for each of your clients. When you log in with multiple users, the accounts and profiles these users have access to are all consolidated into a single profile list, and you can run reports that combine data between profiles from different users

Support for OAuth authentication

When you log into the Analytics module of GA Data Grabber, authenticating with Google Analytics is now done with OAuth. This means that authenticating happens in your Internet browser on a Google webpage, and you never need to enter your login credentials to GA Data Grabber. GA Data Grabber will never have access to your full login credentials, and its access rights are restricted to your Google Analytics data (GA Data Grabber cannot access other parts of your Google Account). You can revoke this access right at any time from your Google Account’s control panel. To provide extra security, GA Data Grabber also uses SSL encrypted HTTPS connections for data transfer. These elements guarantee the your privacy and the safety of your data, and are especially important considering recent reports of vulnerabilities in Google’s ClientLogin authentication, which is used by many other Analytics API tools. See GA Data Grabber’s full privacy policy here.

Reports with dynamic date ranges

In addition to using fixed date ranges, you can now run reports for a dynamic date range, such as the previous full month, year to date, or last 7 days. Whenever you refresh a report that has a dynamic date range, the dates will be automatically updated to cover the chosen period. This makes it even easier to run your periodic reports with GA Data Grabber.

To test these new feature, download the latest version of GA Data Grabber here

GA Data Grabber AdWords module no longer requires a developer token

With the latest version of GA Data Grabber (available here), you no longer need to have an AdWords developer token in order to use the AdWords module. This means that anyone with an AdWords account can now use this great reporting tool! When you have a GA Data Grabber subscription, you can buy AdWords API units through this page, and then use those units to run reports in GA Data Grabber.

(If you have your own AdWords developer token, you can still use that with GA Data Grabber if you wish. In this case, AdWords API usage will be directly billed by Google to your AdWords MCC account. You can enter your own developer token when logging into the AdWords module of GA Data Grabber.)

Google Analytics & AdWords tool for Mac OS X Excel

Since I published the Google Analytics VBA functions for Windows Excel in 2009, lots of people have contacted me hoping to find a similar solution for Mac Excel. After several months of development and testing, we now have this solution ready: Google Analytics and AdWords data can now be fetched directly to an Excel spreadsheet on Mac Office 2011!

We have currently implemented this technology in GA Data Grabber, our sophisticated tool for fetching and visualizing Google Analytics and AdWords data in Excel. You can download the demo version hereGA Data Grabber works with the Mac Excel 2011 (Mac Excel 2004/2008 are not supported), and of course, Windows Excel 2003 and later. All the Windows functionality is available also on Mac, but fetching data is somewhat slower, due to restrictions in Mac Excel.

If you have any questions regarding our Google Analytics solution for Mac Excel, please contact us at info@supermetrics.com.

Screenshots of GA Data Grabber working in Mac Excel

New Google Analytics data available

On Tuesday, Google announced lots of new metrics and dimensions being available through the Analytics API. Most significantly:
  • There are 10 new AdWords dimensions available, such as the ‘matched query’ dimension, which shows the actual search query typed by the visitor that triggered the impression of the AdWords ad.
  • The ‘visitors’ metrics can now be split and filtered with lots of different dimensions, so it’s possible to fetch, for example, visitors by traffic source. Previously the visitors metric could only be split by time.

As always when there’s an update by Google, we have moved fast: these new fields are already available in the latest release of GA Data Grabber! Download the latest version here.

Of course, all of these new data fields are available also with our Excel VBA and Google Docs functions – these don’t even need updating, since all new fields become immediately available when they are released by Google.

AutomateAnalytics In Twitter

Our products such as GA Data Grabber are being constantly improved. To make it easier for you to see when there’s something new, we will begin announcing these updates in Twitter. You can follow us at twitter.com/MTAnalytics

AutomateAnalytics wishes you a happy Christmas!

Validating EU VAT numbers in Google Docs

I’ve recently struggled to learn the tax accounting procedures for intra-European Union trade. One part of this process is obtaining the VAT numbers of all the client companies in EU countries, which must then be verified before sending the forms to the tax office. 

There’s a tool for doing this validation on the EU commission site, but as it only takes one VAT number at a time, it takes quite a lot of effort to go through a long list of clients. To make this a bit easier, I created a custom function for doing the validation in a Google Docs spreadsheet; you can test it here (make a copy for your own use) To use the function in your own spreadsheets, in the menus go to Tools: Scripts: Script Editor and copy everything, then create a new script in your own spreadsheet and paste it there. It would be very easy to make a version of this for Excel too – if you are interested, please contact me by email.

The usage of the function is very simple, just input the VAT number and two letter country code as parameters. If the country code parameter is omitted, the function will assume the first two characters of the VAT number contain the country code. The function will then indicate whether the number is valid or not. For some countries, it will also show the name of the company.

The function screenscrapes the results from the EU commission tool – if that tool is changed then the function may break. Note that I don’t make any guarantees for the accuracy of the results.

Demo version of GA Data Grabber for AdWords now available for download

The free demo version of GA Data Grabber now supports AdWords queries in addition to Google Analytics ones. This means you can now see the kind of data and visualizations this tool will provides before buying. The limitation with the demo version is that it only fetches data for January-March 2010.
You can download the demo version of GA Data Grabber here.

If you have any questions regarding GA Data Grabber, please contact info@supermetrics.com.

Excel functions for the Marchex API

We have developed a new solution for fetching pay-per-call advertising data from the Marchex API to Excel with a set of VBA functions. This provides a great deal of flexibility for pay-per-call campaign analysis, as you are no longer tied to the built-in Marchex reports. It’s also simple to combine the campaign metrics with data from other sources (for example, Google Analytics data, or sales data from your internal systems).

The functions can fetch data such as

  • Number of Calls
  • Unique Leads
  • Domain Referrals
  • Ad List
  • My Numbers

The data can be split by various dimensions; for example, you can fetch the number of calls by date and by campaign. There are many other dimensions available too, such as:
  • Call status (answered, hang-up, etc.)
  • Group
  • Tag
  • Caller name & number

The functions are used in the same manner as our Google Analytics and AdWords functions – they can be used directly on the worksheet like any of Excel’s built-in functions. This makes it very easy to build dashboards that combine pay-per-call data with other metrics such as web analytics or PPC data – all that is required is some basic Excel skills (no VBA knowledge is necessary).

You can test the functions using this file (there’s a free 14 trial)
You can either buy a copy of the functions that you can use to build reports on your own, or hire us to create a complete dashboard for you. For more information and purchasing, please contact info@supermetrics.com.

Fetch up to a million rows of GA data to Excel

We’ve just published a new version of GA Data Grabber, which can fetch up to a million rows of data per profile. While the Analytics API has a limit of 10 000 rows per query, GA Data Grabber now has the ability to loop through up to a hundred queries and combine the data in Excel. This is especially useful when analyzing profiles with a lot of content or dynamically created URLs.

(Note that depending on the type of query, fetching a large number of rows may take a up to several hours.)

You can download the demo of the latest version of GA Data Grabber, purchase the full version, and read more about the app here. (Existing customers can get the updated version for free by contacting mikael.thuneberg@supermetrics.com)

Visualizing changes in popularity of site content

Update: this tool is no longer being developed. For another tool that can do everything this tool can and much more, see GA Data Grabber: GA Data Grabber

I bumped into this post on the SEOmoz blog, and decided it might be a good time to make a new post about a tool we released back in January, but which most people probably don’t know about – it’s designed for conducting exactly the kind of analyses as described in the SEOmoz article.
If you want to see how to popularity of the different content you have on your site has changes over time, your only option is to look at charts like this, which show the pageviews for one URL (or folder containing several URLs) at a time:

These charts are good for checking the popularity of a certain content item, but not very handy if you want to get an overall picture of how things are changing. For this type of analysis, the SEOmoz article advises a manual process of downloading Excel files from GA, combining these and creating charts. Another option is to use my MT Google Analytics Visualizer tool, which works in Excel and does everything for you: it automatically downloads the data through the Analytics API, does the calculations and creates the charts  – all this in a few seconds. You can then see the changes in popularity of your content with charts like this (click to enlarge):

You can select between four different detail levels for the content: plotting by the full URL, or grouping the URL’s into folders of various levels. For example, for the URL “/2010/04/google-analytics-data-to-google-docs.html” the first folder level would be “/2010/”, the second would be “/2010/04/”, and the third would in this case be the same as the full URL, as there are no more sub-folder levels.

Plotted by folder level one, the chart above looks like this:

And the best thing is, you can plot all kinds of stuff, not just content – here’s a chart with traffic source:

There are lots of other possibilities too: some are shown in the original article regarding the tool.
The tool is very affordable at just 59 US dollars, and there’s a free demo version too – click this link to download the demo or purchase the full version.

AdWords API solution for Excel now available

I’m excited to publish a great new solution for fetching AdWords figures to Excel through the AdWords APIsomething that many people have been asking for.
We’ve created two products based on this technology:
1. AdWords module for GA Data Grabber

With our popular report automation tool for Googla Analytics, GA Data Grabber, you now have the option to include an AdWords reporting module in addition to the regular Google Analytics module. All the advanced features of the tool, such as automated charting and PPT creation, can be used also with AdWords reporting. And the best thing is, as the data is already in Excel, it’s very easy to modify the charts, do additional calculations and so on – making this a much more flexible analysis tool than anything else currently in the market. There are few screenshots on the left – click to enlarge.

To download a demo version GA Data Grabber and to purchase the full version, visit the GA Data Grabber site: http://supermetrics.com/
2. AutomateAnalytics Functions
If you love our Google Analytics VBA functions, then this is for you: you can buy a blank workbook that has the VBA code for the AdWords functions embedded, so you can use them to build your own reports, just like with the Analytics functions. More information regarding this solution can be found here. These functions work both in Excel and in Google Spreadsheet.

AutomateAnalytics featured in the GA blog

Today, Google published an article about my business and solutions in the official Google Analytics blog – check it out here!

I’m really happy to be recognized this way 🙂 Lots of thanks for this, and also for the earlier article published last August, to Nick Mihailovski of the GA API team – if he hadn’t shown interest in my solution last summer, almost no one would probably have ever heard about it.

Advanced Web Metrics with Google Analytics, 2nd EditionLots of thanks also to Brian Clifton for dedicating several pages of the recently published 2nd edition of his great book, Advanced Web Metrics with Google Analytics, to my stuff!

Publish Excel data to the net via the Google Charts API

I wrote a VBA function that creates a web chart of an Excel data range. With this, you can publish Excel data to the net instantaneously: just type the function, select the cells where the data is located, and you get the URL for the chart! The only required parameter is the data range, optionally you can also set things like the chart title.

Here’s an example file with some World Cup statistics (sadly, my own country isn’t on the list..)

And here’s a chart I published from that Excel (click to enlarge):

Note that there’s some limit on how much data you can publish with this – I don’t know what it is exactly, but hundreds of rows seems to be too much.

I use Tiny URL to shorten the URLs generated by the function – I borrowed the piece of code for shortening the URLs from here.

If you find this solution useful, please make a donation to support my work:

GA Data Grabber – New version in 3D!

Version 1.1 of GA Data Grabber, the tool that helps you analyze multiple Google Analytics profiles, is now out!

There are several new features that make this tool even more useful for people working with many profiles:

  • New visualizations: The tool now really takes advantage of Excel’s charting capabilities, and lets you look at your data in many ways not seen before!
  • Segmenting by a dimension: Now you can choose one dimension as a “segmenting dimension”, and the tool will automatically split the data by that dimension (generating a pivot table using that dimension as column headers). See attached screenshot, where data is split by week and year, and traffic source is used as the segmenting dimension.
  • Refreshing reports: You can now quickly refresh reports you’ve created, updating the figures every week for example.
  • Linked PowerPoints: The tool can generate PPTs with charts that are linked to the Excel file – when you refresh the queries with new data in Excel, the charts are updated automatically
  • In addition, there are dozens of minor improvements and fixes.

To download a demo version of GA Data Grabber and to purchase the full version, visit the GA Data Grabber site.

Existing customers will receive the update for free – I will contact you by email.

The site is now AutomateAnalytics

I’ve just renamed my site to AutomateAnalytics.com. For quite some time, I’ve thought “Mikael’s Page” wasn’t the best possible name for the site, but haven’t had the time to make the change. So now it’s much clearer from the title and URL what this site is about – of course there’s some content not related to analytics on the site too, but the analytics stuff is what brings me the money, so naming it after that makes most sense for me 🙂

URL’s with supermetrics.com still work also, as all of the content is mirrored there.

Fetching tweets to Excel/Word/PPT/Google Docs

Update: due to changes made by Twitter, this script does not work at the moment. We have published a new version that is now included in our Supermetrics Functions product.

Our project of the day: creating a solution for fetching a list of tweets by keyword from Twitter to Excel. There are lots of Twitter statistics apps out there, but it’s quite nice being able to fetch tweets to Excel, as there you can conveniently do all kinds of additional analysis like sentiment scoring, either manually or with automation, and control all the steps in the analysis process yourself. There you can also merge the results with data from other sources, for instance into a web analytics dashboard created with my Google Analytics functions.

There’s an example workbook where the getTweets function is used available for download here. I put a few Finnish brands there as keywords, change those and it will fetch new tweets. On the second sheet, there’s another example where the optional parameters of the function are used. 

There’s also a Google Docs version of the functions – you can try it out here (it isn’t as stable as the Excel version though – every now and then it returns an error complaining about too many queries). You can also add it to your document through the Google Docs script library via Tools: Scripts: Insert: search for “tweets”. UPDATE: Google Docs version now also includes Tweet URL.

The functions work in Windows Excel 2003 and later – macros need to be allowed in Excel’s security settings (after changing the setting, you may need to restart Excel). The functions also work in other MS Office apps like Powerpoint and Word – I’ll post an example file of that kind of use later when I find the time.
The parameters for the function are:

  • searchTerm (required): word or words to be searched for, search operators can be used
  • maxResults (optional): by default, the function fetches 100 tweets, but this can lowered or increased up to 1500
  • includeMetaData (optional): whether to include tweet date and author – by default, this is set as FALSE, so only the tweet content is fetched
  • includeHeaders (optional): whether to include column headers
  • languageCode (optional): can be used to restrict the query to tweets in a certain language – to do this, type the two-letter 639-1 language code from this list

There are all kinds of possibilities for analyzing and presenting Twitter data in Excel and other MS Office apps – please contact me at mikael.thuneberg@gmail.com if you’d like my help for creating this type of solution for you.

There’s also a getTweetTrend function in the file you can test, it counts how many times the keyword is mentioned per day. However, I’m not too happy with that function, since it’s really slow and since the Twitter API only seems to allow fetching seven days of tweets (and even less in the case of popular search terms).

Google Analytics data to Google Docs

UPDATE March 2014: We’ve published a new Google Docs add-on that makes it very simple to get your metrics from Google Analytics and other sources: Supermetrics for Google Docs
UPDATE: Due to changes by Google, this no longer works. We have a new version available here.

The functions for importing Google Analytics data to a spreadsheet are now also available for Google Docs! With this solution, you can create automatically updating Analytics reports in a GD spreadsheet – these can contain analyses and visualizations that are not available through the GA user interface. You can combine data from several GA profiles, and merge it with data from other systems, such as internal sales data. And having the reports in Google Docs makes it easy to share them within your company or with clients.
Try it now here!  (If you get a “We’re sorry, your spreadsheet cannot be copied at this time” error, open your Google Docs file list, click Create new-> From template -> Public templates, and search for “Google Analytics Functions Examples”)

You can use the functions following the instructions here (they are for Excel but usage is practically the same) and the parameter reference here. There’s also a nice tutorial made by someone else here.

The Google Docs functions also work on a Mac, as well as any other systems from which Google Docs can be accessed – you can even check the latest stats with your mobile.

There are three ways to get started using the functions in Google Docs:

  1. Do it yourself: Copy the function code from here and paste it to a Google Docs spreadsheet file (open the Script editor from the Tools: Scripts menu, paste the code there, and save).  
  2. A customized solution: Put an email to us at info@supermetrics.com describing the kind of report you’d like to see in Google Docs, and I’ll give you price for creating it.

Using the functions in a Google Docs spreadsheet is almost identical to how they are used in Excel: there are the same three functions (getGAauthenticationToken, getGAaccountData and getGAdata), and they take the same parameters as the Excel versions (with a few minor exceptions, which are explained below). The function code is of course different (I’ve converted it from VBA to Google Apps Script), but for the end user this doesn’t make a difference.

Having the GA functions available in Google Docs opens up some nice possibilities. See for example this chart I created using the functions in Google Docs – it’s embedded here to always show the distribution of visits during the last 30 days.

The few differences between the GD and Excel versions of the functions are that in the GD versions, you can specify the maximum number of rows fetched (‘maxRows’ parameter). It seems that GD currently gives an “all our servers are currently busy” error when trying to parse a large XML response, and this can be avoided by setting a limit on the rows fetched. My experience is that this error starts to appear when the result set is over 600 rows. You can also specify a ‘startFromRow’ parameter, to work around the row limit by combining several instances of the function.

Also in other ways, the GD version is less stable than the Excel one – every now and then the authentication doesn’t work, or fetching data gives the “servers busy” error. These are caused by problems in Google’s end, so unfortunately there isn’t anything we can do currently to fix them – but Google Docs is developing rapidly so I’m sure the stability will improve.

The other difference is that the GD version doesn’t yet support fetching conversion goals with the getGAaccountData function – I just didn’t have the time to implement that yet.

If you get an error complaining about “rate limit exceeded”, this is due to too many functions being updated simultaneosly (the GA API only allows 10 queries per second). You can avoid this by staggering the queries so that they are not all fired at the same second; to do this, go to Tools: Scripts: Script editor, and in the gatGAdata function, above the line which has the UrlFetchApp, insert these two rows:

var randnumber = Math.random()*5000;


With this in place, the queries will wait for a random time of between zero and five seconds before being updated, thus it’s less likely that you would hit Google’s limitation of 10 queries per second. If you still have trouble, you can duplicate the second row, this will cause a wait of between zero and ten seconds (and of course, you can put this line there as many times as needed, if you’re still hitting the limit).

The code for these functions is now also available in the Google Docs script library.

In case you have any questions regarding the usage of this solution, please visit our help forum.


GA Data Grabber – The most powerful tool for automating Google Analytics & AdWords reporting

Eliminate time-consuming manual work in data processing and visualization – GA Data Grabber automates all this and helps you keep up with the latest developments for a large number of Google Analytics profiles or AdWords accounts. Works within MS Excel, making it easy do additional analysis and charting.

GA Data Grabber is designed especially for people managing many Analytics profiles or AdWords campaigns, as the regular Google Analytics and AdWords interfaces are not well suited for analysis of several accounts or campaigns.

For up-to-date information and to get the free trial, visit the GA Data Grabber site

Benefits of the tool include:

  • The latest developments for a large number of sites can be checked quickly
  • Regular KPI reporting can be automated, eliminating routine work
  • Makes in-depth analysis more productive: time can be put into analysis and decision-making rather than into manually fetching reports and creating charts
  • Everything happens in Excel, so it’s easy to customize the charts, do additional calculations and combine with data from other sources. As the data is in an Excel table, it can also be easily fed to another analysis tool for additional analysis.

  • Fetches and combines data from any number of GA profiles or AdWords accounts
  • Fetches any metrics that are available through the GA/AdWords APIs (including calculated metrics like bounce rates or average ad positions)
  • Results can be split by dimensions, such as traffic source or search keyword
  • Automatically generates charts & other visualizations from the data
  • Automatically generates PowerPoint presentations of the results
  • Results can be filtered by GA’s ‘advanced segments’
  • Automatically calculates how the figures have changed compared to the previous week or month, or to the same date range a year earlier
  • Works in Windows Excel 2003 and later versions

Screenshots (click to enlarge)


To download a demo version of GA Data Grabber and to purchase the full version, visit the GA Data Grabber site.

GA Data Grabber can be customized if there’s some feature that you would like to have that’s not currently available. In this case, please contact us by email (info@supermetrics.com).

New version of the Google Analytics visualization tool

Update: this tool is no longer being developed. For another tool that can do everything this tool can and much more, see GA Data Grabber: GA Data Grabber

I’ve created a new version of my data visualization tool, MT Google Analytics Visualizer. With this tool you can visualize Google Analytics data in many ways not possible through the GA user interface or with other tools using the GA API. The sophisticated analysis capabilities give you a much deeper understanding on what’s happening on your sites.

A demo version of tool (restricted to three GA profiles, and to data from January-March 2009) can be downloaded here. The full version can be purchased for 59 USD per GA user account here:
(Before buying, test your network connection with the demo version – proxy or firewall settings may prevent the app from making queries)
The biggest change to the first version is the option to plot any dimension on the category axis, instead of just day, week or month. You can also now plot calculated metrics like bounce rates and conversion rates. Advanced segments are also supported. Works in Windows Excel 2003, 2007 and 2010; macros need to be enabled.
The tool is based on my GA Excel functions, the most versatile method of importing Google Analytics data into Excel and other MS Office applications.
With the added metrics and the ability to cross-tabulate dimensions, there’s a large range of interesting analyses that can be done using the tool. Here are a few examples.

Browser and browser version by week: readability of the chart is not that great, but still it’s quite interesting (click to enlarge).

Landing page vs source of new visitors: summarizes on which pages traffic coming from various sources lands.

Average visit length by visit count and connection speed: visitors who have visited the site before stay longer than first-timers, but the average session lengths don’t increase much after the 6th or 7th visit. Visitors with dialup connections have the same pattern but on a lower level.

Tool for visualizing Google Analytics data in a new way

Update: this tool is no longer being developed. For another tool that can do everything this tool can and much more, see GA Data Grabber: GA Data Grabber
To illustrate the kind of stuff that’s possible with my GA-to-Excel functions, I created an Excel application which fetches data from GA and creates charts out of that.
The application can be downloaded here (latest version works also in Excel 2003, though it looks much prettier in 2007).
I think these are a good addition to GA’s built-in charts – using the built-in charts, it’s quite difficult to get a good understanding of how a site’s traffic composition changes over time, as they only display one series at a time. As an example of what my application does, see the image below, which displays the relative country-split of the traffic coming to this site, by week.

While I’m pretty sure the data produced by the application is accurate, this is just something I did very quickly, so please double-check the numbers also in GA, if you’re going to use them for something serious… Note that using the pagepath dimension with a folder level specified may be really slow, because it loops through several queries to get enough data (and if your sites has thousands of unique URLs, the data may anyhow not be fully accurate).

There also an option to apply a smoothing algorithm to the numbers, so it’s easier to spot trends. The Excel function for this LOESS algorithm was created by someone named Nick – I found it from here.

Free Excel function for translating text with Google Translate

UPDATE: Google is shutting down the free Translation API on which this solution depends. Instead, they have published a new paid API that you can access with our new translation add-in. Though it’s not free, it’s not expensive either, and it’s much faster and more reliable than the old free solution. There’s a free trial so you can test before purchasing.

We created a new VBA function that uses the Google Translate API to translate text in Excel (or other MS Office applications). The only input the function requires is the text you want translated, and the code of the language you want it translated to (for example ‘en’ for English). Google Translate can automatically detect the source language, though you may also specify it in the function parameters if you so wish. The code for the function is here, and an Excel file showing it in use is here [Links removed due to the API shut down]. The file also contains a list of supported languages.

Magical self-updating Powerpoint (fetches data from Google Analytics)

Using the Google Analytics VBA functions is by far the most convenient in Excel, but they work in Powerpoint too: this example PPT automatically updates itself with the latest figures from your Google Analytics profile (you need to have macros enabled in Powerpoint). Picture of wizard included.
If you’re interested in getting a customized Powerpoint presentation with always up-to-date figures from your GA profiles, please contact me at mikael.thuneberg@gmail.com.

Function for fetching a list of GA profiles

UPDATE: This function has been replaced by the getGAaccountData function, see http://supermetrics.com/2009/08/excel-functions-for-fetching-data.html
In addition to the functions included in the previous post, I created a third function, getGAprofiles. With this fucntion you can fetch a list of the Analytics profiles to which the authenticated user has access rights. The only required input for the function is the token that is generated by the getGAauthenticationToken function. The function fills three columns, and has to be inputted as an array formula (select the cells, write the function in the formula bar, and press ctrl+shift+enter).
The code for the function is here.

The benefit of this function is that it makes it possible to build dashboards and applications where the profile list is not predefined, but is created dynamically depending on the user’s access rights. I made an example Excel to show how to use this function (with the other two functions) to combine data from three profiles into a graph – just input your Analytics login information and it should work (macros have to be enabled of course)

Excel functions for fetching Google Analytics data

Integrate Google Analytics data into Excel workbooks – no plugin installation needed. Now also available: an advanced reporting tool based on these functions.

There are various solutions for fetching data from Google Analytics to Excel, as this article in Google’s Analytics blog describes. My approach is to use custom functions to achieve this, whereas the other solutions are Excel plugins you need to install. I think the benefits of this approach are:

  1. Speed: No need to install a plugin that slows down Excel
  2. Ease of use: The functions are used just the same as any of Excel’s built-in functions (like SUM or COUNT). No knowledge of VBA is required!
  3. Easy sharing: The code fetching the data from Google Analytics is embedded in the Excel workbook, so you can send the workbook to others, and they can refresh the GA data or modify the queries without them having to install anything
  4. Flexibility: The query parameters can be outputs from other functions or macros; execution of queries can be controlled with macros
  5. Compatibility: Works in Windows Excel 2003, 2007 and 2010 (maybe older versions too, haven’t tested). Also available for Google Docs Spreadsheet. For Mac OS X, we provide Supermetrics Data Grabber, which works with Mac Excel 2011 (in addition to Windows Excel versions 2003 and later).
  6. New API features immediately available: Whenever there are new metrics or dimensions added to the Analytics API, you can start fetching them immediately, without needing to wait for a plugin provider to add those to their tool.
  7. Customization: If you know VBA, you can easily modify the functions to fit your specific needs

Getting started

There two options to get started using my solution to import Analytics data to Excel:

  1. To try out an advanced analysis tool created with this technology, take a look at Supermetrics Data Grabber – it automatically creates charts and PowerPoints of your data, and can be used to automate analysis of Google Analytics, AdWords, BingAds and Facebook data
  2. To design reports on your own using our Supermetrics Functions, download the latest version of  this Excel file and start building from there. Just get an authentication token from http://AnalyticsFunctions.com and copy it to the sheet, and it should automatically load some of your data. I’ve added a few examples on how to use the functions to that file – by modifying it you can create all kinds of reporting solutions. Note that you need to have macros enabled in Excel’s security settings for the functions to work (after changing the settings, you may have to restart Excel).

You can find more information on our product and support pages for Supermetrics Functions.

Lots of thanks for everyone who have helped us develop this by reporting bugs and sharing their ideas.