Sample size & duration calculator
Work out how many visitors your A/B test needs before you start, and how many days that realistically means for your store.
Enter your numbers above.
How to pick your inputs
Baseline rate is your current conversion rate for the metric you're testing, for product page tests that's usually add-to-cart rate, which you can read straight from your analytics. Minimum detectable effect (MDE) is the smallest relative improvement you'd care about: 15% MDE on a 6% baseline means detecting a move to 6.9%. Smaller effects need dramatically more traffic, halving the MDE roughly quadruples the sample.
If the estimated duration comes out at months rather than weeks, don't run a doomed test, read our guide to A/B testing on low-traffic stores for strategies that actually work with less traffic (bigger swings, longer windows, pooled templates).
The formula
This uses the standard two-proportion sample size calculation at a two-sided 5% significance level: n per variant = (zα/2√(2p̄(1−p̄)) + zβ√(p₁(1−p₁)+p₂(1−p₂)))² ÷ (p₂−p₁)². Full explanation in how long should you run an A/B test, and when your test is done, check it with the significance calculator.