Dating operator benchmarks

Benchmarks are useful and dangerous in equal measure. Useful, because they tell you fast whether a model's assumptions are sane. Dangerous, because every product is different and a number copied without context misleads. The ranges below are operator estimates drawn from how paid dating books tend to behave. Treat them as a way to flag what to check, not as targets to hit or beat.

The core benchmarks

Metric Working range What it tells you Monthly churn (one-month plan) 15 to 25 percent Above 25 percent, any long lifetime claim is suspect Free-to-paid conversion 2 to 6 percent Higher in high-intent and niche products CAC payback under 3 months, ideally under 2 Cash recovery speed; governs how fast you can scale Net LTV to CAC floor around 3 to 1, healthy 4 to 1 and up After refunds, fees, and disputes, not gross Dispute rate keep well under 1 percent Above network thresholds, your merchant account is at risk ARPPU tracks near your one-month plan price The number the business actually runs on

How to use them

Read these alongside your own cohort data, never instead of it. If your model sits far outside a range, that is not automatically wrong, but it is a flag. A churn assumption of 5 percent in a one-month dating plan, for example, almost certainly means the model is borrowing a number from general software that does not apply. A net LTV to CAC of eight to one might mean you have a fantastic product, or it might mean you are underspending on growth and leaving the market to a competitor.

The two that most often hide problems are churn and the gross-versus-net gap. Honest monthly churn collapses many optimistic LTV figures, and the deductions for store commissions, fees, refunds, and disputes turn many healthy-looking gross models marginal once netted out. Check those two first.

Why these and not vanity metrics

Downloads, registered users, and total installs are easy to grow and tell you little about whether the business works. The benchmarks here are deliberately the ones tied to cash and to a paying user's real economics, because cash, not headline user counts, is what determines whether a dating business survives and can afford to grow.

A caveat on first-party data

The strongest benchmark you can have is your own. These ranges are a starting point for an operator without a baseline yet. As you accumulate real cohort data, replace these with your own numbers, segmented by market and by side of the marketplace, and benchmark yourself against your past rather than against a generic range.

Related reading

Use these with the dating app unit economics guide and its calculator, and the glossary entries on churn, CAC payback, LTV, and dispute rate.