Fit the curve, don't guess the lifetime
Multiplying ARPDAU by an assumed 90-day lifetime is the most common way mobile teams overstate LTV. A power curve anchored on two real retention points captures the long tail's shape properly and usually lands 20–40% below the naive estimate.
Sanity checks before you bid on this
The output is only as good as the three retention inputs.
- • Compare modelled D7 to actual D7 — a big gap means your cohort isn't a power curve and the projection will drift.
- • Use cohorts of the same acquisition source; blended retention hides bad channels.
- • Net out store and mediation fees before computing LTV, not after.
- • Give organic uplift only what you can attribute; it's the easiest input to inflate.
Payback matters as much as ratio
A 2x LTV:CAC that takes 300 days to realise will starve you of cash long before it makes you money. Pair this with the UA payback calculator and treat both as gates before scaling spend.
Related guides
Long-form playbooks on the same topic, written by the RevenueLab editorial team.
LTV:CAC Benchmarks for SaaS in 2026 (and What 'Good' Actually Means)
What ratios investors look for, why 3:1 isn't always the right target, and how payback period interacts with LTV:CAC across PLG, SMB, and enterprise SaaS.
Read the guideRevenue Model Glossary: 40 Terms Every Operator Should Know (CPM, RPM, ARPU, LTV, CAC, ROAS…)
Plain-English definitions for the 40 revenue-modeling terms that show up across creator, SaaS, ecommerce, and ads — with the exact formula, a worked example, and the most common misuse for each.
Read the guideFAQ
Why fit from D1 and D30 rather than D7?
D1 and D30 bracket the curve, so the fit is stable. D7 then acts as a free validation point — if the modelled D7 is far off your real one, the power-curve assumption doesn't hold for your app.
Should ARPDAU be gross or net?
Enter gross and let the fee input handle it. That way you can flex store and mediation terms without re-deriving your revenue number.
Is 365 days the right horizon?
For most consumer apps, yes — value past a year is heavily discounted and rarely survives a platform change. Subscription apps with multi-year retention may justify longer.
How do I count organic installs?
Use the incremental organic lift measured when you scale spend up or down, not your total organic volume. Anything else double-counts users you'd have got anyway.
How this calculator is built
Independently maintained
Written by Sam Doshi and the RevenueLab editorial team. We don't sell the data feeds this tool is built on.
Sourced from primary data
Benchmarks come from public AdSense / Stripe / IRS disclosures and reader-submitted data — never third-party "$X per view" claims. Full methodology.
Last editorial review
Reviewed on a rolling quarterly cycle. Dated reviews are published on the methodology record for each calculator.
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See our editorial policy and disclaimer. Results are estimates, not advice.