Cohort Explorer

Definition

The Cohort Explorer allows you to measure the performance of various cohort definitions over time and across multiple performance measurements.

Cohorts

The Cohort Explorer supports three different cohort definitions:

1. New Customers: The count of new customers first seen by RevenueCat in a given period, cohorted by their First Seen Date.
2. Initial Conversions: The count of customers first converting to any product (including paid or unpaid, and subscription or one-time purchase) in a given period, cohorted by their Initial Conversion Date.
3. New Paying Customers: The count of customers making their first payment in a given period, cohorted by their First Purchase Date.

📘Comparing New Paying Customers with Subscriptions

Please keep in mind that a the count of New Paying Customers and Subscriptions started in a given period will likely differ, since one customer may have multiple subscriptions over their lifetime, or may convert to paid through a one-time purchase instead of a subscription.

Comparing cohort definitions
Each cohort definition is a unique way of grouping customers together to understand how each unique cohort performs over time.

Because these measures each have unique cohort definition, each period references different groups of customers. For example, the Apr '24 cohort of New Paying Customers may include some customers who happened to also be first seen in Apr '24, and are therefore in the Apr '24 cohort of New Customers, but it may also include some customers who were first seen in prior months.

In addition, the Apr '24 cohort of New Customers may include customers whose first payment won't occur until after Apr '24.

Therefore, these different cohort definitions should not be thought of as a conversion funnel for the period they reference. Rather, they are independent ways of grouping customers together to understand how each unique cohort performs over time.

Measures

The Cohort Explorer supports four different measures that can be used to understand the performance of your chosen cohort over time:

1. Revenue: The amount of revenue generated in a given period by that cohort.
2. Realized LTV: The cumulative amount of revenue generated by that cohort since their inception until a given period.
3. Realized LTV / Customer: The cumulative amount of revenue generated by that cohort since their inception until a given period, divided by the count of customers in that cohort.
4. Retained Subscriptions: The count of subscriptions from that cohort which remain active as of a given period. (This count can go up over time if some members of the cohort start their subscription late, or if more customers reactivate in a given period than the number who churned)

📘

The count of "customers" in that cohort refers to whichever cohort definition is being used. So when looking at a cohort of New Paying Customers, Realized LTV / Customer will divide Realized LTV by the count of New Paying Customers.

Available settings

• Filters: Yes
• Segments: No

How to use the Cohort Explorer in your business

The Cohort Explorer can be used to answer many different questions, like:

• At an average CAC of $x, what is my typical time to payback? (Realized LTV / Customer by New Customer Cohorts)
• What is my revenue retention of the customers who first paid in the last year? (Revenue by Paying Customer Cohorts)
• How can I expect Realized LTV to grow over time for my most recent paid customer cohorts based on the performance of my prior cohorts? (Realized LTV / Customer by Paying Customer Cohorts)
• What portion of my Initial Conversions become paying customers that remain paid after a given period of time? (Retained Subscriptions by Initial Conversion Cohorts)

Calculation

Examples for each measure:

Revenue of New Customer Cohorts
For each period, we:

1. Count the New Customers that were first seen in that period
2. Provide the sum of revenue generated by that cohort in each subsequent period

Realized LTV of Paying Customer Cohorts
For each period, we:

1. Count the New Paying Customers that made their first payment in that period
2. Provide the cummulative sum of revenue generated by that cohort as of each subsequent period

Realized LTV / Customer of Paying Customer Cohorts
For each period, we:

1. Count the Paying Customers that made their first payment in that period
2. Provide the cummulative sum of revenue generated by that cohort as of each subsequent period, divided by the count of Paying Customers in that cohort

Retained Subscriptions of Initial Conversion Cohorts
For each period, we:

1. Count the Initial Conversions that made their first purchase or started their first subscription of any kind in that period
2. Provide the count of subscriptions that were active from that cohort as of each subsequent period

FAQs

Question	Answer
How are refunds handled in the Cohort Explorer?	When we see a refund processed by a store, we deduct the revenue from the associated transaction, and that revenue will therefore be deducted from the period it was originally reported in when measuring Revenue and/or Realized LTV. In addition, refunded transactions will not be included when measuring Retained Subscriptions.
How can the Cohort Explorer be compared with Subscription Retention?	When using the Active Subscriptions measure in the Cohort Explorer, it is fundamentally measuring the same thing as absolute Subscription Retention, but keep in mind that the Subscription Retention chart is always segmented by Product Duration so that the retention periods always reflect expected payment periods.
Why might Realized LTV in the Cohort Explorer and the Realized LTV charts not be identical?	There are two expected reasons for differences between these charts. First, in the Cohort Explorer we're measuring what happened within a given period. Another way to think about that is that we're measuring what was true by the end of that period. So Realized LTV as of "Month 2" in the Cohort Explorer is actually measuring what was true by the end of Month 2. The Realized LTV charts, on the other hand, are measuring what was true by a given date. So Realized LTV as of "3 Months" refers to the beginning of Month 3. In addition, these two charts may refresh at different times, and therefore the data will be slightly different as a result.