Cohort Report Builder

Have you ever wanted to study how different subsets of your users behave over time? For example, ever wondered if users who register during a promo period have a higher average lifetime revenue than those who do not? If the answer is Yes, then the Cohort Report Builder is the perfect tool for you. Adobe Commerce Intelligence is optimized to perform this analysis and make it relevant to your business.

What is cohort analysis?

Cohort analysis can be broadly defined as the analysis of user groups that share similar characteristics over their life cycles. It allows you to identify behavioral trends across different user groups.

For an in-depth primer on cohort analysis, review this page.

In your Commerce Intelligence dashboard, it is easy to create user cohorts based on a cohort date and a metric in your account.

Well, why is cohort analysis important?

As mentioned above, cohort analysis allows you to identify behavioral trends among different user groups. With a solid understanding of how certain groups behave, you can tailor your decisions and spending to maximize your sales. For example, take a lifetime revenue cohort analysis - while this kind of analysis is beneficial for many reasons, the immediate one is better customer acquisition decisions.

How do I create my own cohort analysis?

New Architecture

These are the instructions for using the Cohort Report Builder on the New Architecture.

Adding a Metric

Now that you are in the Report Builder, add the metric that you want to perform the analysis on (example: Revenue or Orders).

Toggle the Metric View to Cohort

This opens up a new window to configure the details of the Cohort Report.

Five specifications are needed to build a Cohort report:

1. Grouping cohorts

Cohorts are grouped by a timestamp, like registration date or first order date.

2. Cohort time period

Choose the time period to group cohorts by. In other words, which part of the timestamp that you selected above is most important; the week, month, quarter, or year? Your report displays data in whatever interval that you select here

3. and 4. Set the number of cohorts to view and how much data each cohort must have

These parameters help you view only the cohorts that you are interested in, and the handy Preview box at the bottom of the window shows you exactly what cohorts display in your report.

By default, the current cohort is not included unless you change the minimum amount of data required for each cohort to 0. In this case, the cohort for the current time period includes only partial data.

5. Time Range After Cohort Occurrence

This feature allows you to set the time range of data that you view for the selected cohorts. For example, if you want to view 24 monthly cohorts based on customer's first order date, but you are only interested in the first 3 months of data for each cohort, you can set the number of cohorts to view to 24 and the time range after cohort occurrence to 3.

The interval for this value changes with whatever you selected in the cohort time period and the value is set to 12 by default; the value does not change unless you click on the calendar icon to edit it.

Other notes

Example

Here is an example to pull it all together. In this example, I want to check out order behavior after a cohort’s first purchase to see if that cohort is coming back to make repeat purchases in the next six months.

Legacy Architecture

Legacy Architecture

Below are instructions specific to the legacy version of the Cohort Report Builder. If you are interested in using the new version, see New Architecture for more information about migrating to an Commerce Intelligence New Architecture account.

How do I create my own cohort analysis?

Cohort analysis in action! Here, you can see revenue growing over time on a cumulative and per-user basis.

This section walks you through creating your own cohort analysis. For examples (and animated GIFs demonstrating the process), look at the Examples section of this topic.

Adding a metric

Now that you are in the Cohort Report Builder, add the metric (example: Revenue or Number of orders) on which you want to perform the analysis.

Selecting the cohort date

The next step is to specify the cohort date. This is the date by which your users are grouped. For example, this might be User's first order date or User's registration date.

Setting the interval and time period

Next, set the Interval and Time Period.

Interval
The Interval option allows you to set the length of your cohorts. For example, if this is set to Month, your report is measured in months.

You can change how these intervals are displayed on the x-axis using the Duration menu.

Time Period
Use the Time Period menu to choose the specific user cohorts to analyze. You can show every cohort, choose from a list, specify a time range, or define a rolling time range of cohorts to include. For example, if you used the Specific Cohorts option, you can select specific months to include in the analysis:

If you are grouping you cohorts by registration date and then selected April, May, and June in the Specific Cohorts list, any users who registered in those months would be included.

Defining the X-axis

Under duration, you can define the chart’s X-axis settings. That is, how many time periods each data point represents and how many data points to include in the analysis.

Selecting the counting members table

If you opted to group users by a cohort date that has been joined from another table, you may see a counting members in the … table option.

Look at an example to understand this setting. Suppose you built a report cohorting a Revenue metric by Customer's registration date. You also wanted to use the perspective Average value per cohort member to see the revenue per buyer over time. To find the average value per buyer, you need to decide on the number of buyers to divide by. Is it the number of registered customers in your customers table, or is it the number of distinct buyers in your orders table for the same period?

This setting answers that question. Counting members in the customers table includes all customers (whether they made a purchase, ever) in the average. Counting members in the orders table includes only customers who made a purchase.

Selecting a perspective

After you have defined the metric and how you want to analyze it, you can select the perspective you want to use.

Just above the report visualization is a dropdown of perspective settings.

See Perspectives.

Examples of cohort analysis

Now that you have gone through how to create a cohort analysis, look at some examples.

I want to know how my user cohorts are growing over time.

In this example, you analyzed the Revenue metric, grouped your cohorts by the customer's first order date, and selected the 8 most recent cohorts (defined in the Time Period menu) to include in the analysis. To see how the cohorts grew over time, you used the Cumulative Average Value per Cohort Member perspective.

I want to know, on average, how many orders a user makes at different points in their lifetime.

![Average number of orders users make at different points in their lifetimes](…/…/assets/cohort2.gif

For this example, you analyzed the Number of orders metric, grouped your cohorts by the customer's first order date, and included the eight most recent cohorts (defined in the Time Period menu) in the analysis. To see the average number of orders for each cohort, you changed the perspective to Average Value per Cohort Member.

I want to understand how a user’s future purchasing activity compares to their first month’s activity with the business.

Perspectives

Standard
This shows the incremental contribution of a given cohort group at any given point in their life cycle. (example: The “Week 6” point displays all data points made by users in their sixth week.)

Average Value per Cohort Member
This divides the Standard cohort analysis in (1) by the number of users in each cohort group. This can be useful for comparing cohort performances on an apples-to-apples basis, as not all cohort groups may include the same number of users. For example, the average week 6 revenue per user from a certain cohort.

Cumulative
This perspective shows the traditional cohort analysis on a cumulative basis. In other words, it shows the total contribution of a given cohort to date at any given point in their life cycle. For example, the cumulative revenue after six weeks of users from a certain cohort.

Cumulative Average Value per Cohort Member
This divides the Cumulative analysis in (3) by the number of users in each cohort group. It shows the average lifetime contribution (often average lifetime revenue) per cohort member at each period in the cohort's life. For example, the average lifetime revenue after six months of users that joined in June.

Percent of First Value (show first value)
This analyzes the aggregate cohort contribution at a specific time in a cohort's life cycle as a percentage of their contribution in the first period. For example, the month 6 revenue divided by the month 1 revenue of users that joined in June.

Percent of First Value (hide first value)
This is the same as the perspective above, except that the first time period value of 100% is hidden.

Wrapping up

The Cohort Report Builder is optimized for grouping users by a common cohort date. You might be interested in grouping the users by a similar activity or attribute. Adobe recommends checking out this tutorial on qualitative cohorts to get started.