What is Cohort Analysis?
A technique that groups users by shared characteristics or time periods (cohorts) to analyse behaviour and outcomes over time, revealing patterns that aggregate metrics hide.
Understanding the Details
Cohort analysis reveals trends that averages obscure. Instead of looking at all users together, you group users by when they signed up (January cohort, February cohort) or by characteristic (enterprise cohort, SMB cohort). Then you track each cohort's behaviour over time. This reveals whether retention is improving with each new cohort, which acquisition channels produce better long-term customers, and how product changes affect different user groups. Cohort analysis is essential for understanding whether your business is actually getting healthier.
How It Works in Practice
Retention cohorts
Tracking each month's signup cohort shows whether recent cohorts retain better than older ones.
Channel cohorts
Grouping customers by acquisition channel reveals that paid search customers churn 2x faster than organic.
Feature cohorts
Users who use feature X in first week retain 50% better than those who don't.
Why It Matters
Aggregate metrics can improve while your business gets worse (or vice versa). Cohort analysis reveals whether changes are actually improving outcomes for comparable groups of users.
What People Often Get Wrong
Overall metrics tell the full story. Actually, cohort analysis often reveals that averages hide significant variation.
Cohort analysis is only for large companies. Actually, even small companies benefit from understanding cohort patterns.
You need special tools for cohort analysis. Actually, spreadsheets can do basic cohort analysis effectively.
How We Handle Cohort Analysis
We implement cohort analysis for key metrics like retention and LTV, helping companies understand whether they're actually improving and which factors drive better outcomes.
Related Terms
Common Questions
Need Help With Cohort Analysis?
If you'd like to discuss how cohort analysis applies to your business, we're happy to explain further.