A/B Test Calculator
Calculate statistical significance for your A/B tests instantly
Control (A)
Variant (B)
Results
Enter visitors and conversions to see results
How it works
This calculator uses a two-proportion z-test to determine whether the difference between two conversion rates is statistically significant. A p-value below the chosen significance threshold (α) means the result is unlikely to be due to chance. Aim for at least 100 visitors per group for reliable results.
Frequently asked questions
What p-value means statistically significant?
At 95% confidence (the standard), p < 0.05 is significant. This means there is less than a 5% probability the observed difference is due to random chance. Use 99% confidence (p < 0.01) for high-stakes decisions.
How many visitors do I need for an A/B test?
It depends on your baseline conversion rate, minimum detectable effect, and desired power. As a rough guide: a 5% baseline with a 10% relative improvement requires ~7,000 visitors per group at 95% confidence. Use a sample size calculator before launching.
What is relative uplift vs absolute change?
Relative uplift is the percentage improvement over the control rate. If control converts at 5% and variant at 5.5%, absolute change is +0.5 pp and relative uplift is +10%. Relative uplift is more meaningful for business impact.
What does the confidence interval mean?
The confidence interval shows the range of plausible values for the true difference. If the interval does not include 0, the result is statistically significant. A wide interval means you need more data.