Cohort Analysis
Also known as: Cohort Retention AnalysisCohort TrackingRetention CohortsUser Cohorts
💡The Concept
Cohort analysis groups customers by their signup date (or another shared attribute) and tracks their behavior over time. Instead of looking at blended metrics that mask trends, you see how each 'class' of customers performs independently. A SaaS company with 5% monthly churn might discover that January cohort churns at 3% while March cohort churns at 9% — the blended 5% hides a deteriorating acquisition quality problem. Amplitude found that companies using cohort analysis identify retention problems 6-8 weeks earlier than those using aggregate metrics.
⚠️The Trap
The trap is treating all customers as one pool. Blended metrics create dangerous illusions: your overall retention might look stable at 85%, but if Q1 cohorts retain at 95% and Q4 cohorts retain at 70%, you have a ticking time bomb. By the time blended metrics show the drop, the damage has compounded for months. Another trap: analyzing cohorts too narrowly (daily) creates noise, or too broadly (annually) hides actionable trends. Monthly cohorts are the sweet spot for most SaaS businesses.
🎯The Action
Build a cohort retention table: rows = signup month, columns = months since signup. Calculate retention rate for each cell. Look for two patterns: (1) Vertical drops — if a specific cohort has abnormally low retention, investigate what changed in acquisition that month. (2) Diagonal patterns — if ALL cohorts drop at month 3, you have an onboarding or value-delivery problem at that stage. Target: Month 1 retention ≥ 80%, Month 12 retention ≥ 50% for healthy SaaS.
⚡Pro Tips
Overlay cohort retention curves on top of each other. If later cohorts have better curves, your product is improving. If curves are getting worse, your product-market fit may be eroding or your acquisition channels are attracting lower-quality users.
Revenue cohorts matter more than user cohorts. A cohort that retains 70% of USERS but 110% of REVENUE (via upsells) is outperforming a cohort that retains 90% of users but only 85% of revenue.
Run cohort analysis on engagement (not just retention). A cohort whose weekly active usage drops from 5 sessions to 2 sessions is signaling future churn even if they haven't canceled yet.
🚫Common Myths
✗Myth: “Cohort analysis only matters for subscription businesses”
✓Reality: E-commerce companies like Amazon and Shopify merchants use purchase-frequency cohort analysis to track repeat purchase rates. Any business with repeat behavior benefits from cohort analysis — including marketplaces, gaming, and media.
✗Myth: “You need thousands of customers for meaningful cohort data”
✓Reality: Cohort analysis is useful with as few as 50-100 customers per cohort. The patterns (retention curves) are remarkably consistent even at small scale. Slack used cohort analysis when they had just a few hundred teams.
📈Industry Benchmarks
Month-1 Retention Rate
B2B SaaS (monthly cohorts)Elite
> 90%
Good
80-90%
Average
65-80%
Needs Work
50-65%
Critical
< 50%
Source: Mixpanel 2024 Product Benchmarks Report
Month-12 Retention Rate
B2B SaaS (monthly cohorts)Elite
> 60%
Good
45-60%
Average
30-45%
Needs Work
15-30%
Critical
< 15%
Source: Lenny Rachitsky's SaaS Retention Benchmarks, 2024
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