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Practical guide to cohort ltv model: formulas, workflow, implementation pitfalls, and a direct execution playbook with Unit Economics Calculator.
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Scenario modeling for CAC, LTV, margin, and net profit with growth lever prioritization.
The formula LTV = ARPU x Margin / Churn gives you one number. But that number blends all customers together — power users who stay 3 years and trial churners who leave in month 1. Cohort analysis separates them and shows the real retention curve.
A cohort is all customers acquired in the same period (usually month). Track what percentage remains active each subsequent month:
| Month | Jan Cohort | Feb Cohort |
|---|---|---|
| 0 | 100% | 100% |
| 1 | 82% | 87% |
| 2 | 71% | 79% |
| 3 | 65% | 76% |
| 4 | 63% | 74% |
| 5 | 61% | 73% |
| 6 | 60% | 72% |
Jan cohort retains 60% at month 6. Feb cohort retains 72%. That 12-point gap matters enormously at scale.
What could have changed between Jan and Feb?
Overlay product and marketing events on cohort data to find cause and effect.
User cohorts track retention by headcount. Revenue cohorts track dollars retained — and they can diverge. If surviving users expand (upsell), revenue retention can exceed 100% even as user retention drops. This is net revenue retention (NRR).
Example: Jan cohort has 60% user retention at month 6, but those remaining users upgraded plans. Revenue retention at month 6 = 85%. The 25-point gap is pure expansion revenue.
Model cohort-level unit economics in the Unit Economics Calculator. Related: CAC Payback Period.
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This article is reviewed by the Tools Hub editorial team for factual accuracy, practical relevance, and consistency with current product workflows.
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