What is Cohort Analysis?
Cohort analysis groups users who share a characteristic — most commonly the time they signed up — and tracks how each group behaves over its lifetime. Instead of looking at one blended average, you compare cohorts side by side to see whether the product is improving.
This is powerful because aggregate metrics hide trends. Total active users might look flat while a retention cohort chart reveals that newer cohorts retain far better than older ones (or vice versa), telling you whether recent changes are working.
PMs use cohort analysis to measure retention, diagnose churn, and evaluate the long-term effect of changes. For example, comparing the day-30 retention of cohorts before and after an onboarding revamp shows its true impact better than a short-term spike.
Examples
- A retention curve shows the post-redesign cohort retains 40% at day 30 versus 28% for prior cohorts.
- A PM segments cohorts by acquisition channel and finds paid users churn faster than organic.
Where PMs use this
Related terms
Retention
The degree to which users keep coming back to a product over time — the foundation of sustainable growth.
Churn Rate
The percentage of customers (or revenue) lost over a given period — the inverse of retention.
DAU / MAU
Daily and monthly active user counts; their ratio (DAU/MAU) is a common measure of engagement stickiness.
A/B Testing
A controlled experiment comparing two versions to see which performs better on a chosen metric.