Estimate the visitors required in each variant of a two-group conversion experiment. The calculation uses a two-sided normal approximation with equal allocation and accounts for the baseline conversion rate, minimum detectable relative lift, confidence level, and desired power.
This is a two-sided, equal-allocation normal approximation.
The main result is the minimum rounded-up sample for each variant. Smaller effects and higher confidence or power require more observations.
This fixed-horizon estimate does not correct for repeated peeking, multiple metrics, clustering, or traffic imbalance.
At a 10% baseline, 10% relative lift (11% variant rate), 95% confidence, and 80% power, the calculator requires 14,751 users per variant under this approximation.
It uses the inputs, formula, units, and independence assumptions shown on this page. Change the inputs to match your own system or experiment.
Use representative averages for planning, preserve headroom where applicable, and test multiple plausible scenarios instead of relying on one point estimate.
No. The result is a planning estimate. Validate it with measured data, monitoring, load tests, or an experiment-design review as appropriate.
The calculator checks values required by the formula and displays an error instead of returning NaN or Infinity. Valid zero values remain available where they are meaningful.
Tools may use different statistical approximations, unit conventions, rounding rules, priors, confidence definitions, or operational headroom assumptions.
| Variable | Unit | Meaning |
|---|---|---|
| Baseline p₁ | proportion | Control conversion probability |
| Alternative p₂ | proportion | Baseline × (1 + relative lift) |
| n | users/variant | Equal-allocation fixed-horizon sample |