Cohort analysis groups customers by acquisition period (e.g., Jan 2024 signups) to track retention, revenue, and behavior over time. Shows if your product is getting better or worse at retaining customers.
Cohort analysis is THE most important retention metric. Group customers by when they signed up (cohorts), then track what % stay active month-by-month. Example: Jan 2024 cohort—100 customers signed up. Month 1: 80 active (80% retention). Month 2: 60 active (60% retention). Month 3: 55 active (55% retention). Month 6: 50 active (50% retention). Plot this for every monthly cohort side-by-side to see trends: Are newer cohorts retaining better (product improving)? Or worse (product-market fit declining)? Ideal cohort curve: Steep drop month 1-2 (onboarding friction), then flattens out (loyal users stay). Bad cohort curve: Continuous decline, never flattens (no loyal user base). Segment cohorts by: Acquisition channel (organic vs paid—organic typically retains better), customer type (enterprise vs SMB), pricing plan (annual vs monthly). Use cohort analysis to: Measure product improvements (did new onboarding increase Month 2 retention?), predict LTV, identify best acquisition channels, justify pricing changes.
Tracks cohorts religiously. Found users who created playlists in Month 1 had 2x higher Month 12 retention. Changed onboarding to push playlist creation—retention jumped 30%.
Jan cohort: 100 users → 80 (Month 1) → 70 (M2) → 65 (M3) → 60 (M6) → 55 (M12). Flattens at 55%. Clear loyal user base. Can predict LTV accurately.
Every cohort drops from 100 → 50 → 25 → 10 → 5 by Month 6. Never flattens. No PMF. Shut down despite raising funding.
Without cohort analysis, vanity metrics hide problems. You might add 1,000 users/month but lose 1,200 (net negative). Cohort analysis reveals true retention, lets you calculate accurate LTV, shows if product changes improve or hurt retention.
Month 2: >40% is good signal. Month 12: >30-40% is excellent (means loyal user base). If Month 6 retention is <20%, likely no PMF—users don't find value.
Monthly for high-growth startups. Quarterly for mature companies. Need at least 3-6 months of data before cohort curves stabilize and show patterns.
Red flag. Newer customers retaining worse than old = product quality declining, wrong target market, or competition improved. Must investigate and fix urgently.
StartupIdeasDB has 3,000+ validated problems to help you build the next big thing.
Browse Problems →