A/B Test Significance Calculator
Check whether the difference between two conversion rates is statistically significant, with p-value and uplift.
Statistically significant at 95% (p = 0.0091, z = 2.61). Variant B looks like a real change.
Two-proportion z-test, two-tailed. A rough guide for A/B experiments — not a substitute for a full statistical review.
What Is the A/B Test Significance Calculator?
The A/B Test Significance Calculator tells you whether the difference between two variants is real or just noise. Enter the visitors and conversions for A and B and it computes each conversion rate, the relative uplift, a two-proportion z-score and p-value, and a plain-English verdict on whether the result is significant at 95% confidence.
How It Works
Enter visitors and conversions for the control (A) and variant (B). Rates, uplift, p-value and a significance verdict update instantly.
When to Use It
When running website, email or ad A/B tests and deciding whether you have a real winner or need more data before shipping a change.
Frequently Asked Questions
- What test does it use?
- A two-proportion z-test (two-tailed), the standard approach for comparing two conversion rates. It flags significance at the common p < 0.05 (95%) threshold.
- Why does it say collect more data?
- If the p-value is above 0.05 the difference could be chance. Larger sample sizes make true differences easier to detect.
Last reviewed: 2026-06-27