Calculate required sample size and statistical significance for email A/B tests. Input open rates, click rates, and confidence levels.
Email A/B Test Calculator answers two connected questions for a campaign split: how much traffic a planned open-rate or click-rate comparison needs, and whether an observed A-versus-B difference clears a selected confidence threshold. It works with proportions, keeping opens and clicks as separate outcomes. The frequent mistake is judging a percentage gap without the recipient counts behind it. A 2 percentage-point lift can be inconclusive in a small send and highly significant in a much larger one.
In sample-size planning, an open or click is treated as a yes-or-no outcome for each eligible recipient. The calculator applies the baseline and comparison rates plus the selected confidence setting to report the needed test volume. Read any power, allocation, or tail convention shown on the page, because those choices change the requirement even when the two rates stay fixed.
Significance evaluation needs the observed rate for each email version and the number of eligible observations behind each rate. The rate gap is assessed against sampling variation at the selected confidence level. Rates of 10 percent and 12 percent from small sends do not carry the same evidence as those rates from large sends, so preserve the actual A and B denominators.
No. Two percentages do not reveal how much data supports them. Supply the A and B sample counts required by the calculator, using the same denominator definition for both variants. If you have only rounded dashboard rates and no underlying counts, the result cannot be reconstructed reliably, especially when the observed difference is small.
No. In a standard significance test, 95 percent confidence is not a posterior probability that B will win. It indicates that the observed difference meets the procedure's error threshold under its assumptions. It also says nothing by itself about business value, so inspect the absolute percentage-point change and expected campaign impact.
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