Cohort analysis is tracking groups of customers who share a common characteristic or starting point to see how their behavior changes over time. You might track everyone who became a customer in January 2024 as one cohort and everyone from February 2024 as another cohort. Then you compare retention rates, revenue per customer, engagement, and other metrics across cohorts to identify patterns and improvements. This is way more useful than just looking at overall averages because it shows you whether your business is actually getting better at retaining customers and generating value over time.
Why Averages Lie To You
Looking at average customer lifetime value or average retention rate across your entire customer base hides what’s actually happening in your business. You might have early customers from two years ago with amazing retention inflating your numbers while recent customers are churning fast. Cohort analysis reveals this by showing you that January 2024 customers had 80% retention at six months but June 2024 customers only had 50% retention at the same point. Now you know something changed and you can investigate what broke instead of assuming everything is fine because your overall average looks okay.
Using Cohorts To Make Decisions
The real power of cohort analysis is using it to measure the impact of changes you make. If you improve onboarding in March, you can compare March cohorts to February cohorts and see if retention actually improved. If you raise prices in Q2, you can track whether those customers have different LTV or churn characteristics than Q1 customers. Without cohort analysis, you’re making changes blind and hoping they work. With it, you have proof of what’s working and what’s not based on how real groups of customers behave over time.