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A/B Test Calculator - Statistical Significance

Determine if your A/B test results are statistically significant. Know when you have a real winner and can confidently scale the better variant.

Enter Test Results

Variant A (Control)

Visitors

Conversions

Variant B (Test)

Visitors

Conversions

Confidence Level

Test Results

Sample Size Calculator

Estimate how many visitors per variant you need before running your test.

Baseline Conversion Rate (%)

Minimum Detectable Effect (%)

Sample Size Recommendation

A/B Test Calculator FAQ

Statistical significance means the difference between your variants is unlikely due to random chance. A result is typically considered significant at 95% confidence - meaning there's only a 5% chance the difference is random.

Generally, you need at least 1,000 visitors per variant for meaningful results. The exact number depends on your baseline conversion rate and the minimum detectable effect. Smaller differences require more data.

Run tests for at least 1-2 full business cycles (typically 2-4 weeks) even if you reach significance earlier. This accounts for day-of-week effects and traffic variations. Never stop a test early based on preliminary results.