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A/B Test Sample Size Calculator

Inputs

Baseline Conversion Rate(%)

Current conversion rate as a percentage (0-100%)

Minimum Detectable Effect (Lift)(%)

Smallest improvement you want to detect as a percentage (e.g., 10% for 10% relative lift)

Significance Level (Alpha)(%)

Probability of Type I error; typically 0.05 for 95% confidence

Statistical Power (1 - Beta)(%)

Probability of detecting true effect; typically 80% or 90%

Number of Test Groups

Total groups including control (e.g., 2 for A/B test, 3 for A/B/C test)

Sample Size Per Group

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Number of visitors needed in each test group

Total Sample Size Required

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Effect Size (Cohen's h)

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Critical Z-Score

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Formula

n = (Z_α + Z_β)² × p(1-p) / h² × k / (k-1), where h = 2 × arcsin(√p₁) - 2 × arcsin(√p₀)