Design incrementality tests, read the results honestly, and reconcile the conflicting numbers your platforms, MMP, and finance team all report. Built for post-ATT mobile UA, where last-click attribution quietly lies.
Sample size (proportions). Two-proportion normal approximation: n = (z₁₋α/2·√(2·p̄(1-p̄)) + z₁₋β·√(p₁(1-p₁)+p₂(1-p₂)))² / (p₂-p₁)², where p₂ = p₁·(1+MDE). Unequal splits inflate the total by 1/(4·s·(1-s)).
Sample size (revenue). n/arm = 2·(z₁₋α/2+z₁₋β)²·CV²/MDE². Revenue is heavily skewed, so the coefficient of variation (CV) does the heavy lifting; CV of 3-6 is typical for mobile ARPU.
Reading a test (proportions). Lift = rate_test − rate_control. Standard error √(p_c(1-p_c)/n_c + p_t(1-p_t)/n_t), a two-sided z gives the p-value, and ±1.96·SE gives the 95% confidence interval.
Bayesian readout. Each arm's true rate gets a Beta(conv+1, non-conv+1) posterior. We draw 8,000 Monte-Carlo samples to get the probability the test arm is genuinely better and the credible interval of the lift. This is what stays useful when traffic is too thin for a clean p-value.
Incremental economics. Incremental conversions = (rate_test − rate_control)·n_test, i.e. only the conversions the ads actually caused. iCPI = spend / incremental conversions; iROAS = incremental revenue / spend. The naive version counts every exposed conversion as caused, which is the over-counting the platforms bank on.
Reconciliation. Each source is bias-corrected (value ÷ bias) then combined as a trust-weighted average: Σ(corrected·weight)/Σ(weight). The band is the spread of corrected values. It's an opinion with structure, not a measurement.
The honest limit. A calculator designs and reads tests; it can't run a clean holdout for you, and a contaminated split produces confident nonsense. At very low spend, no test can detect realistic lifts. The tool will tell you when you're in that zone instead of pretending otherwise.
Single file, no dependencies, nothing leaves the browser. A companion to the LTV & ROAS Modeler — model the LTV, measure the incrementality, trust one number.