Definition
Cohort-based LTV estimates lifetime value using observed retention and gross profit over time for a cohort, rather than a simple churn formula.
How to use it
- More accurate when churn changes over time or expansion is meaningful.
- Use cohorts by plan/channel to avoid mixing behaviors.
Measured as
Measure Cohort-based LTV on the same customer segment, time window, and revenue basis each time you review it.
Operator takeaway
- More accurate when churn changes over time or expansion is meaningful.
- Use cohorts by plan/channel to avoid mixing behaviors.
- Keep Cohort-based LTV consistent by cohort, segment, and period before you use it as a decision signal in planning or reporting.
- Interpret the metric alongside retention, margin, or payback so one ratio does not hide the real operating trade-off.
Next decision
- Quantify the impact with Cohort LTV Forecast Calculator if you need to turn the definition into an operating assumption.
- Read Cohort LTV forecasting: churn, expansion, discounting (practical model) if the decision depends on interpretation, policy, or trade-offs beyond the raw formula.
Where to use this on MetricKit
Calculators
- Cohort LTV Forecast Calculator: Estimate cohort-based LTV using churn, expansion, gross margin, and optional discounting.
- Retention Curve Calculator: Model a simple cohort retention curve (logo retention) and translate it into expected revenue and gross profit over time.
- Two-stage Retention Curve Calculator: Model a retention curve with different churn rates for early months vs steady-state, and estimate expected value over time.
- Unit Economics Dashboard Calculator: Compute a unit economics snapshot: gross profit LTV, CAC payback, LTV:CAC, and break-even targets from a few inputs.
- Cohort Payback Curve Calculator: Estimate when a cohort pays back CAC using a simple retention curve (two-stage churn) and optional expansion.
Guides
- Cohort LTV forecasting: churn, expansion, discounting (practical model): A practical guide to cohort-based LTV: why it beats simple churn formulas, how to choose assumptions, and how to interpret discounted LTV.
- Cohort vs aggregate metrics: why averages can mislead: Aggregate metrics hide churn and expansion dynamics. Learn when to use cohort analysis and how to interpret retention and LTV.
- LTV guide: formula, customer lifetime, cohort models, and LTV:CAC: A practical LTV guide covering shortcut formulas, gross profit vs revenue LTV, customer lifetime, cohort-based models, and how to connect LTV to CAC and payback.
- Retention curves: how to read them and why they matter: A practical guide to retention curves: what they show, how to interpret churn vs retention, and how to connect retention to LTV and payback.
- Two-stage churn: modeling early drop-off vs steady-state retention: A practical guide to two-stage churn models: why early churn matters, how to model it, and how to connect retention improvements to LTV.