📧 Email Marketing

A/B Test Sample Size & Power Calculator

Determines the minimum sample size and expected test duration to detect meaningful lifts in open, click or conversion rates with statistical confidence.

Running underpowered A/B tests that produce inconclusive results Wasting time on tests that take too long or are statistically invalid Difficulty translating business-relevant lift into actionable test designs

Compute required sample size per variant and estimated duration given traffic.

Baseline conversion rate (percent of visitors) Minimum detectable relative lift (percent, e.g. 10 = 10%) Significance level α (%) Desired power (%) Daily visitors per variant (traffic allocated to each arm)