Planet RoadmapAggregate metrics can be misleading. If your overall retention rate stays flat while you are growing rapidly, it might mask the fact that newer cohorts retain much worse than earlier ones. Cohort analysis solves this by grouping users based on when they signed up or when they first experienced a change, letting you compare apples to apples over time.
What Is a Cohort?
A cohort is simply a group of users who share a common characteristic within a defined time period. The most common type is a time-based cohort: all users who signed up in January form one cohort, February sign-ups form another, and so on. You can also create behavioral cohorts based on actions users take, like completing onboarding or upgrading to a paid plan.
By tracking each cohort separately over time, you can see whether your product is getting better or worse at retaining users, independent of growth fluctuations.
How to Read a Cohort Chart
A cohort retention chart is typically a table where each row represents a cohort and each column represents a time period after the cohort's start date. The cells show the percentage of users still active. Reading down a column tells you how a specific time period has changed across cohorts. Reading across a row tells you how a single cohort decays over time.
- Improving columns (top to bottom) mean your product changes are working.
- Flattening rows mean users who stick around for a few weeks tend to stay long-term.
- A steep initial drop followed by a flat line suggests an activation problem, not a retention problem.
Using Cohort Analysis to Evaluate Features
When you launch a significant feature, compare cohorts from before and after the launch. Did the post-launch cohort retain better at week four? Did they activate faster? This is one of the most reliable ways to measure whether a feature made a real difference, because you are controlling for the timing of when users arrived.
Pair your cohort data with qualitative feedback. If retention improved after a launch, check your feedback portal to understand why. When retention drops, feature requests and support tickets often explain what went wrong.
Getting Started with Cohort Analysis
You do not need a sophisticated analytics platform to start. Most product analytics tools support basic cohort views out of the box. Begin with monthly sign-up cohorts and track weekly retention for the first eight weeks. This alone will reveal patterns that aggregate dashboards completely miss.
As you get comfortable, experiment with behavioral cohorts. For example, compare retention between users who set up a public roadmap in Planet Roadmap within their first session versus those who did not. These comparisons help you identify the onboarding steps that matter most.