The Cohort Retention Analysis panel allows you to accurately measure product retention and stickiness over time. Product retention measures the percent of users within a cohort that interact with your API in some way and then return continue to interact with your API. Unlike subscription retention which merely tracks whether a customer has an active subscription, product retention tracks whether users are coming back actively use your product.
If you’re not familiar with retention analysis, you should first read Chapter 3 of API Analytics: The Ultimate Guide to Grow Your Platform Business eBook
In order to start a retention analysis, you need to decide on initial and returning criteria. By default, any activity is considered, but you can specific criteria based on API fields or user actions.
For example, if you are building a payments API, you can set the initial API call to a customer’s first
POST /payments and then
the returning call a second
These filters set up the criteria for the first action and returning action. The results chart is broken down by cohort date in the vertical direction (date of first action). For each row which is a single cohort of users, you can see the percentage of users performing the returning action for each interval after the cohort date.
In the picture, we are showing daily retention, which means day 1 signifies one day after the cohort date, day 2 is two days after the cohort date, and so on.
If instead you selected weekly or monthly retention interval, then a user will be counted for week 1 if they performed the returning action any day of the following week after the cohort date.
For example, if you’re showing daily retention, then your user base is segmented into daily cohorts based on when they performed the first API call.
You can also define which users should be included in the retention analysis. For example, you may want to look at only users located in the United States.
New Users will filter each cohort by only new users. New Users is helpful to measure how sticky your adoption funnel is while excluding users who are already long term customers (hence already likely to have high retention rates). N
A powerful feature of cohort retention analysis is the ability to see how retention curves vary by a user property such as by demographic information or acquisition channels. Any properties stored with a user or company profile are available under Group By.