Cohort Retention Calculator

Cohort retention: grouping users by acquisition date

Cohort retention groups users by the date you acquired them, then measures what share is still active at t = 1, 7, 30 days (mobile) or M1, M3, M6 (SaaS). The formula is retention(t) = active(t) / cohort_size. Say you bring in 1,000 users in January and 300 are active on day 1, 150 on day 7, 100 on day 30. That works out to D1=30%, D7=15%, D30=10%, roughly the mobile average reported by Adjust/Apsalar. The strongest apps, like WhatsApp and Instagram, push D30 above 50%. What you want to see is the smile curve: retention drops, then flattens out, and a flat tail is the sign of product-market fit. On the SaaS B2B side, a GRR (Gross Retention) above 90% is healthy, and an NRR (Net Retention, expansions included) above 110% puts you among the best. As Sequoia likes to put it, "retention is the king".

Applications

Use it to confirm PMF (Product-Market Fit) before you pour money into acquisition, to run cohort analysis in Mixpanel/Amplitude, and to make go/no-go calls on features and verticals. It also helps you zero in on the ICP (Ideal Customer Profile) where retention runs highest, and the smile-curve heuristic tells you at a glance whether a product holds onto a stable core of users or just keeps leaking.

FAQ

Why cohorts and not a single overall metric? Aggregate retention buries timing effects. A flood of new users can hide churn happening in the older cohorts. Splitting things into cohorts keeps each acquisition group separate.

What is a "smile curve"? Retention drops sharply at first, then levels off into a flat tail, or even ticks back up as dormant users come back. A flat tail sitting above zero is the clearest PMF signal you'll get.

GRR vs NRR? GRR counts only churn and downgrades, so it caps at 100%. NRR folds in expansion revenue from your existing customers, which lets it climb past 100%; the best SaaS companies land at 120% or more.