Multi-Line for Cohort Retention — Day-1 to Day-90 Retention Curves
A cohort retention multi-line chart plots the percentage of surviving active users ($R_{c}(t) \in [0, 100\%]$) over elapsed time since signup for multiple cohorts to detect product-market fit (where $dR/dt \to 0$).
Tip: Paste Excel or Google Sheets rows (Ctrl+V / ⌘V) directly into any cell.
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Cohort c retention at horizon t: R_{c,t} = (ActiveUsers_{c,t} / InitialCohortSize_c) * 100%. Terminal retention lift = R_{New,6m} - R_{Old,6m}.
Chart Design & Use-Case Tips
- 01Cohort c retention at horizon t: R_{c,t} = (ActiveUsers_{c,t} / InitialCohortSize_c) * 100%. Terminal retention lift = R_{New,6m} - R_{Old,6m}.
- 02True product-market fit is proven when a cohort retention curve stops declining and flattens horizontally into a long-term asymptote (e.g., leveling off at 40% from Month 2 to Month 6).
- 03When a newer cohort (Series A) sits structurally higher than older cohorts (Series B & C) at every time horizon, your product and onboarding improvements are compounding.
- 04Always start Day 0 at 100% for all cohorts.
Frequently Asked Questions
What does a flattening retention curve indicate?+
When the slope of the retention curve approaches zero (flattens horizontally), you have found a core retained user base that continues using the product indefinitely.
What if the retention curve keeps sloping downward toward zero?+
A curve that trends steadily toward 0% without flattening indicates leaky product-market fit—marketing spend will churn out until core habit loops are fixed.
How does onboarding impact the retention curve?+
Better Week-1 onboarding shifts the entire curve upward at Week 1, which typically lifts the long-term Month-6 plateau proportionally.