A/B Test Calculator — Statistical Significance
Enter the number of visitors and conversions for each variant — the calculator will compute conversion rate, difference, and statistical significance (95% confidence level).
Frequently asked questions
What is statistical significance in A/B tests?
Statistical significance (p-value < 0.05) means there is a 95% probability that the difference between variants is not due to chance. If p-value > 0.05 — collect more data; the result is not reliable.
How much data do you need for an A/B test?
Minimum: 100+ conversions per variant. For low-conversion pages (< 1%) you may need thousands of visitors. Run the test for at least 2 full weeks to account for seasonal traffic fluctuations.
What is the difference between 95% and 99% confidence level?
95% (p < 0.05) is the standard for most marketing tests. 99% (p < 0.01) is used when the cost of error is high: pricing changes, critical UX decisions. The higher the confidence level, the more data you need.
What does "lift" mean in an A/B test?
Lift is the relative improvement in conversion rate of variant B compared to control A. For example, if CR_A = 2% and CR_B = 2.4%, the lift is +20%. This is not the absolute difference in percentage points (0.4%), but the relative change.
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