6-MINUTE READ · By Ana Kostic on August 30 2016.
As a PPC marketer, 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.
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.
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 Google Ads 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.
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 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 specialized in international and multilingual campaigns. Passionate about PPC, Online Marketing, Reporting and Data Analysis. You can find her on Twitter or LinkedIn.