Ecommerce analytics 101: A marketer’s guide to driving more online sales with data

Ecommerce businesses generate a ton of data—from your online store to social media to paid ads to influencer marketing. While this wealth of data means you have better opportunities to find meaningful insights, unless you understand ecommerce analytics, you’re missing out on using data to drive more sales.

In this article, we’ll discuss the basics of ecommerce analytics and show you how to lay the groundwork for a solid ecommerce data strategy.

Skip ahead:

• What ecommerce metrics should you track
• How to build a solid foundation for ecommerce analytics
• How top brands are using data to drive more sales
• Tips for ecommerce reporting
• Ecommerce trends you should know about
• A free ecommerce dashboard for Looker Studio

What ecommerce metrics should marketers track

Campaign performance metrics

Impressions, click-through rates (CTR), and cost per click (CPC) tell you how individual campaigns and channels drive traffic and help people discover your online store. You can use this data to allocate marketing budgets more effectively.

From what we’ve seen working with different ecommerce brands, ensuring proper naming conventions is the key to accurate tracking and enabling better campaign optimization.

Website performance

Loading time, product page views, the numbers of add-to-cart and initiated checkouts, etc., help you understand customer behavior, identify bottlenecks, and improve your ecommerce conversion rate. For example, if you have many initiated checkouts but not many conversions, it could be that your page takes too long to load or the checkout process isn’t easy and straightforward.

New vs. Returning customers

By knowing the revenue generated from different customer segments, you can tailor your marketing and retention strategies accordingly. Typically, it costs more to acquire new customers than to drive more sales from your existing ones. For example, you can create a referral program and encourage your loyal customers to share your products on social media. Or show your appreciation by sending discounts or special offers on special occasions—such as their birthdays or Black Fridays.

Total sales

To understand your total sales, you need to understand gross and net sales. Gross sales is the total revenue without any deductions. On the other hand, net sales include gross sales minus discounts, returns, and sales allowances.

Let’s say you own an online fashion brand. If the price of a t-shirt is $50 and you sell 200 items in January, Your gross sales would be: 200 x 50 = $10000

Now, if 200 t-shirts were sold, 20 had a 10% discount, and some customers weren’t happy with the size, so they asked for a return, resulting in $1000 worth of your product. 

Then, in that case, your net sales would be: 10000-(20×5)−1000 = $8900

Combining gross and net sales lets you get a more comprehensive and accurate overview of your business performance and make better forecasting decisions. You can also break down total sales per transaction and per item to get a more detailed view. This requires tracking each transaction correctly with a unique ID.

Customer lifetime value (CLV)

CLV is the estimated revenue from a customer over time. It can be calculated using detailed user-level data, such as the number of customers, their conversion rates, and purchase history.

If your CRM is properly organized—with each deal assigned to the correct account and each account containing detailed information on contact persons, purchasing flows, website interactions, and purchase history—you can conduct cohort analysis and calculate lifetime value.

In case you don’t have a CRM, you can combine data from Shopify and Google Analytics 4 and focus on key metrics such as total sales, items sold, revenue per item, and the distinction between new versus returning customers. Although individual tracking isn’t possible, you can still analyze transactions based on different customer groups and calculate their CLV.

How to build a solid foundation for ecommerce analytics

Having a lot of ecommerce data means more opportunities to explore it and drive meaningful insights. On the other end of the spectrum, you may get lost in the weeds and struggle to manage and know what data is relevant for you. To make your data work for you, you need to have three things in place—people, tools, and processes.

Hire the right people for the job

First, you need to identify the roles and responsibilities within your team. Ask yourself questions such as:

• What kinds of challenges are you trying to solve, and do you have the resources to solve them?
• Who’s responsible for the data and reports?
• What’s your vision for the future?

For small ecommerce businesses, it’s usually one marketer who takes care of everything from campaign ideation to execution to analytics. The problem is that they won’t be able to keep up with everything because they’re spreading themselves too thin. So, in the long run, it’s wise to invest in a team that can help you understand and use data effectively.

Choosing the right tools as you scale

When it comes to ecommerce analytics, you don’t only have the marketing platform data. You also have CRM/sales/orders data to report on, which means that choosing the right tools and establishing the right processes is essential. In a podcast episode, Bartosz Scheiner, our Lead Analytics Consultant, discussed the concept of the marketing analytics lifecycle and how to choose the right tools for the job depending on your analytics maturity.

Early stage (low analytics maturity)

Typically, in this case, we see that people may not have any data and marketing analytics background. It’s usually one person running the operations. The data management is then fairly simple and limited. You don’t have massive amounts of data or complex questions to answer yet. 

The main goal is tracking ecommerce performance and monitoring essential metrics like spend and campaign performance. You can use Google Sheets and Excel for reporting or the native reports the marketing platforms provide.

Mid-market stage (growth and scaling)

Let’s say your business is doing well and expanding into different marketing channels, and you have several campaigns running simultaneously. You may also invest in brand marketing and look at your marketing in different funnel stages—top, mid, and bottom.

The focus at this stage is multi-channel marketing reporting. There’s a need to compare and analyze performance across platforms and campaigns. Tools like Looker Studio or Power BI are great ways to consolidate and visualize ecommerce data and help your team get on the same page. You should keep your spreadsheets or use them as a layer between the data sources and your dashboards. This way, you can take advantage of the spreadsheet’s functions and capabilities for analysis while speeding up your final dashboards.

Enterprise stage (high analytics maturity)

At this point, you have too much data to fit into any databases. Perhaps you want to explore customer segmentation by analyzing your web tracking data—whether it’s Google Analytics 4, Adobe Analytics, or first-party data. You’ll need an ecommerce data warehouse to do the tasks above. 

Another problem you may run into is everyone starts to get their data into their spreadsheets, potentially creating their versions of business reality. A data warehouse solves that problem by centralizing management, applying business logic centrally, and defining KPIs in one place for everyone to consume and draw from.

So, every report that uses your data warehouse as a source has the same numbers and exact same ground truth for everything. On top of that, you can add a BI tool to visualize data and build dashboards.

Processes

Then establishing well-defined, clear, and scalable processes helps ensure effective analytics and reporting. You want to have a process for the following:

• Proper tracking and tagging: maintain consistent transaction IDs, correctly record source and medium information, and adhere to campaign naming conventions.
• Data integration: establish processes for integrating various data sources, such as CRMs, ecommerce platforms, and analytics tools, is essential. This allows for a comprehensive view of customer interactions and sales, enabling better analysis and reporting.
• Creating and updating ecommerce reports: ensure that reports are built on accurate and up-to-date data, with a clear understanding of what each metric represents. Especially during peak season, you need real-time data to optimize and steer your campaigns in the right direction immediately.
• Collaboration and communication: make sure you have frequent check-ins and reviews with your data team. Marketing and data alignment helps to figure out your analytics challenges and make sure you’re working toward the same goals.

Tips for effective ecommerce analytics and reporting

Like any marketing report, your ecommerce report should provide insights into your current performance and help you decide the best next steps. Here are our tips to make sure your reports are actionable.

• Automate ecommerce reporting: manual reporting leaves room for human errors and mistakes. It slows down your time-to-insight, which is critical to optimizing your campaign during critical moments, such as peak season. You can use a tool like Supermetrics to get ecommerce data into your favourite reporting tool.
• Make sure everyone is aligned on your goals: connect your campaign goal to the overall business goals and make sure your team understands the big picture. If not, you’ll find yourself veering into another direction that isn’t aligned with your strategy.
• Set up a CRM: start by building a CRM to capture detailed user-level data. Properly tag deals, accounts, and contacts to track purchase flows and conversions, allowing cohort analysis and lifetime value (LTV) calculations.
• Use data warehouses for large datasets: While Google Sheets and Looker Studio may be sufficient initially. But when you generate more data from different sources and/or explore advanced and detailed analysis use cases, a data warehouse is a must.
• Have a good process for campaign naming conventions: We can’t stress this enough, but following strict naming conventions for marketing campaigns will save you a lot of headaches when reporting and mapping data.

Use an automated ecommerce dashboard to stay on top of your performance during Black Friday and peak season.

How top ecommerce brands use data and analytics to improve your ecommerce performance

HP monitors global marketing performance

Hewlett Packard (HP) is a multinational IT company with a presence in 185 countries worldwide. To monitor their global marketing performance, the team automatically pulls all cross-channel data into Google Sheets, where they can use advanced calculations to analyze large datasets. Then, for reporting, they build a dashboard in Looker Studio. This way, they can share data with people who need it.

Pascal Coulier, Performance Marketing Manager for EMEA at HP, says, “These help us understand our investments and their ROIs and identify blind spots. These insights are essentials for forecasting and steering the campaigns in the right direction.”

Read more about the HP case story.

Benefit Cosmetic use rating and review data to develop targeted local strategies

Benefit Cosmetics a global beauty leader with over 8,000 stores. The marketing team uses rating and review data from Google Business Profile (Google My Business) to assess performance across its numerous doors, employing two primary metrics as “stop lights” to guide their actions:

• % of Doors with 10+ reviews: indicates market performance based on the percentage of doors with a substantial number of reviews.
• % of Doors with a +4 rating: reflects market performance based on the percentage of doors with a high rating.

They categorize market performance using these metrics in a stop-light format, with red indicating low performance, yellow indicating mediocre performance, and green indicating high performance. These insights help Benefit develop targeted strategies—such as increasing marketing spend, making operational adjustments, or launching customer experience initiatives.

Read more about the Benefit Cosmetic case story.

Swappie does budget simulations and forecasting, which improves ROAS by 15%

Swappie is the leading platform for buying and selling refurbished phones. The team combines online and offline marketing data in their BigQuery data warehouse, where they can transform, organize, and prepare it for modeling. They set up a marketing mix model that helps analyze different investment scenarios:

• Channel efficiency forecast: shows them how a channel’s performance evolves—when it’s most and least efficient—and the certainty of the prediction.
• Budget stimulation forecast on sales: shows them the sales at different budget levels and how much they should spend on each channel.
• Optimal investment point: shows how much they should spend in a channel to be profitable.

Using these simulations, the Swappie team can adapt their marketing strategy, make smarter investment decisions, and improve their ROAS by 15%.

Read more about the Swappie case story.

Ecommerce analytics trends you should be aware of

Here are some major shifts affecting how ecommerce brands track and analyze their performance

• First-party data: invest in a first-party data strategy will help you have more detailed and reliable information on your customers, including transaction history, repeat purchases, and user interactions. Especially when privacy is the new norm and third-party data tracking is losing effectiveness. First-party data will become your differentiator.
• Historical data and trend data: while historical data is needed for benchmarking and long-term trend analysis, you should follow current trends and be as agile as possible.
• New emerging platforms: we’re seeing new ecommerce platforms, for example, TikTok Ads. Marketers need to learn how to use these new platforms and analyze campaigns from TikTok or other platforms. 
• Influencer marketing data: it’s crucial to have proper tracking mechanisms in place to capture data from influencer marketing campaigns. This could include referral tracking or other methods to ensure that when an influencer makes a video, you can track its performance and include the statistics in your ecommerce reports.

Track your ecommerce performance with a free Looker Studio dashboard

Ecommerce analytics is not a set-and-forget process. Start with something simple and then iterate it as you go. For example, you can use this automated ecommerce dashboard in Looker Studio to analyze and track what campaigns drive the most conversions.

In case you have a more specific use case in mind, use Supermetrics to get, transform, and manage data in your go-to reporting tools—whether it’s Google Sheets, Looker Studio, or BigQuery.