A/B test significance calculator
Enter each variant's visitors and conversions. We run a two-proportion z-test and tell you whether the difference is statistically significant, or just noise.
Enter your numbers above.
How to use this calculator
"Conversions" is whatever your primary metric counts, for product page tests we recommend add-to-cart events. Use unique visitors per variant, not pageviews, and only read the result once your test has reached the sample size you planned with the sample size calculator.
What the numbers mean
The calculator runs a two-sided, two-proportion z-test. The p-value is the probability of seeing a difference at least this large if the two variants actually performed identically. By convention, results are called statistically significant when p < 0.05, i.e. 95% confidence. If that's new to you, our plain-English guide to statistical significance covers it without the maths degree.
One important caveat: checking significance repeatedly while a test runs (and stopping the moment it flashes green) badly inflates false positives. Decide your sample size up front, then evaluate. More on that in common A/B testing mistakes and how to analyze results.