Most popular e-commerce reports

Each area of business has its own special reports that reflect its marketing realities. Below, we’ll look at the most common reports for e-commerce and retail.

Before you build reports, make sure you have two things:

1. Quality data to analyze
2. An attribution model that takes into account the peculiarities of your business

An overall report allows you to quickly evaluate the effectiveness of your entire marketing department. Set up your report and monitor your department’s goals daily.

Thanks to an overall report, you can quickly see your main indicators and adjust actions in the marketing channels based on their current efficiency. An overall report is suitable to show at a meeting to non-marketing colleagues.

For an overall report, you must configure data collection from:

• Google Analytics
• Advertising services
• CRM and call tracking systems

What metrics and parameters should you pay attention to for this report? Discover them in our article on what indicators your business can’t survive without.

In the example report above, you can see a clear comparison of the performance of all marketing channels. This allows you to immediately assess the growth of traffic and leads thanks to running campaigns.

A big advantage of such reports and dashboards is that they can be automatically updated at the necessary frequency. This means that a sharp drop or rapid growth won’t be a surprise to you at the end of the month.

Online ads affect sales in physical stores. The only question is, do you know the exact numbers? The ROPO indicator varies depending on the goods, region, and customer demographics.

To avoid accidentally turning off a successful online ad campaign that brings many offline customers, use ROPO analysis. According to OWOX BI data, return on ad spend (ROAS) typically increases by 30% to 70% when the ROPO effect is calculated.

The essence of ROPO analysis is to link the behavior of users on the website with their purchases in a physical store. For this purpose, you need:

• Data on on-site actions of website visitors
• Data from your CRM system (orders, returns, transactions)

And, of course, you need a user ID that allows you to merge information about your customers’ online and offline activities. You can read more about the data you need for ROPO reports in our Help Center.

The screenshot above presents a ROPO report. This dashboard helps you answer questions such as:

• Which online campaigns most motivate users to shop offline?
• What percentage of total revenue comes from ROPO sales?
• Which channels bring the most of ROPO revenue?

If an item doesn’t sell well online, don’t rush to remove it from your store. First, check your ROPO report. Maybe this item is a great offline seller. How to use the data you obtain from your ROPO analysis is up to you. But what you’ll definitely be able to do with it is make more informed decisions about distributing your budget based on online and offline data.

Different customer cohorts behave differently. So your approach to them must be different. But first, it’s necessary to understand what the differences are between cohorts and how you can benefit from those differences.

Cohort analysis allows you to see how different cohorts of buyers behave over time and understand how and with whom to work, what to improve, and where. With cohort analysis, you can:

1. Better estimate the return on ad spend for businesses with a long sales cycle
2. Predict and increase customer lifetime value (LTV)
3. Evaluate A/B test results

For cohort analysis, you need to know:

• The criteria by which the cohort will be defined
• The time interval over which your cohorts will be defined: day, week, month
• The reporting period
• Which indicator will be key to the analysis (LTV, ROI, retention rate, etc.)

In this example of a cohort analysis we can see how the revenue for user attraction cohorts changes over time.

The simplest version of a cohort report can be made using Google Analytics or Google Sheets. You can read more about cohort analysis on our blog.

How do you know how much profit you get from your customers over time? Will it pay off to attract a new customer? To figure that out, calculate customer lifetime value (LTV).

The LTV indicator helps you predict likely future revenue and shows you how much money you should spend on a particular customer or group of customers throughout their lifetime with your service. In the case of e-commerce, the customer lifetime is the time during which a customer makes purchases in the stores. Moreover, according to Forbes Contributor Patrick Hull, the probability of selling goods to an existing customer is 60% to 70%. But there’s only a 5% to 20% probability that a new user will buy something.

There are three methods of calculating a customer’s lifetime value:

1. Historical
2. Predictive
3. Traditional

Depending on the method you choose, you’ll need data on:

• The number of customers for the selected period
• Total revenue for the selected period
• The average number of transactions per month
• Total returns per month
• The coefficient of outflow of customers
• ARPU (average revenue per user)
• The average cost of an order
• The average coefficient of profitability
• The average customer life cycle in months
• The average discount size

You can build an LTV report from the General Value tab in Google Analytics. Note, however, that your report will only be accurate if you have real data on customer behaviour, which is not available in Google Analytics. 

We’ve demonstrated five easy ways to calculate the lifetime value of a customer. Choose the option that suits you!

An RFM (recency, frequency, monetary value) report helps you find out which buyers make your business the most profit. With this report, you can analyze customer behavior: how often customers buy and how much they buy from you. This data will also help you understand how to set up personalized marketing for your business.

Customers change their behavior over time, and it’s important to know how to take advantage of these changes. With RFM analysis, you can create your own base of loyal customers and set up personalized communications for different segments.

For RFM analysis, you’ll need data on:

• Sales limitations (when purchases were made)
• Purchase frequency (how often customers purchase something)
• Revenue (total value of purchases)
• User ID

Identifying users is a difficult task. The best way to do it is to use the anonymous OWOX User ID. Unlike the tracking code in Google Analytics, the OWOX User ID allows you to both analyze the intersection of audiences across domains and receive data even when Google Analytics cookies have been deleted or replaced.

With User ID data, you can divide buyers into groups to understand who’s buying your goods and how often. For example, customers can shop:

1. Often and a lot
2. Often and a little
3. Seldom and a lot
4. Seldom and a little

You can use either Google Sheets or OWOX BI to calculate RFM. For more on this, read our article on how to conduct RFM analysis.

It’s important not to forget that stock levels, holidays, and seasonality have a great impact on data. However, for a low cost, an RFM report helps you take a personalized approach to customers, leading to increased profits.

All customer activity on your site should result in a purchase. You may have a successful ad campaign that leads to a lot of targeted traffic, but if visitors fail to move items to the cart.

With a site micro-conversion report, you can understand the weaknesses in your website’s sales funnel. If a buyer doesn’t move to the next step of the funnel, you’ll know how you might encourage them. For example, if a user has made a micro-conversion but has not purchased anything, you can send them personalized ads or emails.

You need to identify exactly what micro-conversions customers can complete on your site and track them. For e-commerce, these can be:

• Searching for an item in a category
• Adding an item to the cart
• Subscribing to mailings
• Reviewing goods
• Scrolling through pages

The example report shown above allows you to quickly detect and resolve conversion activity slips on your site. This report is extremely useful for both marketers and the development team.

It’s hard to imagine e-commerce without stock and a sell-off. Online stores use internal banners to advertise promotions. And, of course, these ads should be monitored in the same way as external advertising.

To attract even more customers, you need to evaluate the effectiveness of your internal advertising campaigns and improve them for your future promotions.

Google Analytics reports data on internal campaigns when Enhanced Ecommerce is enabled. Learn how to turn on Enhanced Ecommerce in the Google Help Center.

You can view the following data in this report:

• Names of internal campaigns
• Number of views
• CTR of internal campaigns
• Transactions
• Revenue

Like the micro-conversion report, the internal banner report helps you boost overall conversions on the site.

Advertising from cost-per-action (CPA) partners can bring up to 20% of traffic to a site. The CPA model of advertising is effective, but in this sphere there’s a high level of fraud. Partner CPA activity reports can save your budget.

By analyzing your CPA partners, you can achieve absolute transparency. Thanks to this information, you can see the efficiency of the traffic you’ve received and estimate the impact of affiliate traffic on other sources.

Such a report requires unsampled data on the behavior of users on your site. We recommend using OWOX BI Pipeline for collecting this data. Then, with the help of the OWOX BI Smart Data service, you can get completed reports.

This report shows the number of transactions with source changes for each campaign. A large number of such transactions means a high probability of source substitution. It’s worth paying special attention to the work of partners with lots of source changes in order to avoid possible deception.

For a complete list of reports to identify unscrupulous CPA partners, visit our Help Center. With these reports, you’ll be able to find out which sources and channels don’t bring value and which partners use brand requests in advertising. And, most importantly, you’ll find out who you should pay.

In order to make decisions on managing the advertising budget, marketers need a report on the effectiveness of advertising based on real sales.

It’s often the case that users make an order but never buy it. To get real sales data, you need to analyze purchases.

For an accurate report, you’ll need data on user behavior on your site (complete and not sampled), merged with data from your company’s CRM system.

This report helps you to increase the ROI of your advertising campaigns without increasing costs.

This report is needed to evaluate the effectiveness of traffic to landing pages.

With this report, you can understand which pages (and what content) most effectively turns visitors into buyers.

1. Cost data from different advertising services
2. Raw unsampled data on users’ behavior on your site
3. Data on purchases from your CRM system

As with the micro-conversion and internal banner reports, information from landing page reports helps you increase overall conversions on the site and increase revenue. 

Read more about ROAS analysis in terms of campaigns and other parameters that are important to your business on our blog.

Before you create any report, you need to make sure you have all the data you need, that you can trust this data, and that you’re aware of all the nuances of your selected attribution model. To do this, you need to answer a few simple questions:

• What attribution model am I currently using?
• Do I understand the risks of using Google Analytics (Last Click attribution)?
• Do I understand all the disadvantages of using the model I’ve chosen?

A detailed overview of all the attribution models on the market will help you choose the one that’s best for you. And if you want to understand what attribution means in marketing, read our next article.

Want the reports you saw in this article? Try OWOX BI. You'll see how you can use it to solve your marketing analytics problems.