The model
Revenue per install, month n = conversion × net price × (1 − churn)^(n−1) Cumulative through month n = conversion × net price × (1 − (1 − churn)^n) ÷ churn Lifetime value per install = conversion × net price ÷ churn Payback month = first n where cumulative ≥ CPI
With a $3.50 CPI, 4% install-to-paid conversion, $9.99 monthly price, 30% commission, and 8% monthly churn, an install is worth about $3.50 over its lifetime — exactly break-even, with payback never quite arriving. Move conversion to 6% and payback lands in month 10. That sensitivity is the point: the payer rate is the lever, and it is a product and onboarding lever more than a media one.
Per install, not per payer
Subscription dashboards love LTV per paying customer because it is a big number. It is the wrong number for acquisition decisions: you paid for every install, including the 96% who never subscribe. Dividing by payers makes a channel with cheap, low-intent installs look identical to one with expensive, high-intent installs. Per-install LTV is what CPI can be compared to; the glossary entry on LTV covers the distinction.
Model first, then measure
Use this to decide whether a channel is worth testing and what CPI you can afford. Then let the cohort matrix take over: realized D30 and D90 revenue per install replaces the model's estimates as cohorts mature. The mechanics of reading that matrix, including the immature-cohort trap, are in D30 realized LTV from cohorts. For the margin side, see the break-even ROAS calculator.
Common questions
- How is LTV calculated for a subscription app?
- Per install: install-to-paid conversion rate × net monthly price ÷ monthly churn. That gives the average lifetime revenue an install generates after the store's cut. Per paying subscriber, drop the conversion rate — but that figure cannot be compared to CPI, because CPI buys installs, not payers.
- What is CAC payback period?
- The time until a cohort's cumulative revenue equals the spend that acquired it — the month where cohort ROAS crosses 1.0x. It turns the LTV:CAC ratio into a cash question: how long is money out before it comes back.
- What is a good LTV:CAC ratio for mobile apps?
- The SaaS rule of 3:1 is a starting point, not a law. What matters is the LTV window: a 3:1 ratio at D365 and a 0.6:1 ratio at D30 can describe the same healthy app. Decide the acceptable payback period from cash constraints, then back out the ratio.
- Why does the calculator use monthly churn instead of retention curves?
- Because monthly churn is the number subscription platforms report directly and most teams know. Real retention is not perfectly geometric — early churn is higher — so the model is optimistic in the first months and roughly right over the lifetime. Replace the D30 and D90 outputs with realized cohort numbers as soon as you have them.
Related terms: payback period, LTV:CAC, churn rate, trial conversion rate.