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A/B Test Sample Size Calculator

Estimate how many visitors each variant needs to detect a lift in conversion rate, and how many days that takes.

Inputs

The control's current rate.
In percentage points: 1 means 5% → 6%.
Chance of calling a difference that is not there.
Chance of catching the effect if it is real.
Across all variants; gives the test length.

Result

Per variant
—
Total visitors
—
Rate to detect
—
Days to run
—
z values (alpha, power)
—

Enter the baseline rate and the smallest change worth detecting.

Runs in your browser; nothing you enter leaves this page.

How it works

The method

It uses the usual two-proportion z-test. You give the baseline conversion rate, the smallest lift worth detecting (in percentage points or as a percent of the baseline), the significance level and the power. The tool returns the visitors needed per variant.

The total is that number times the variants, and if you enter daily visitors it also gives the days the test must run.

n = (zα·√(2p̄(1−p̄)) + zβ·√(p₁(1−p₁)+p₂(1−p₂)))² ÷ (p₂−p₁)²

Choosing the inputs

Significance 0.05 and power 0.8 are common defaults. A one-tailed test needs fewer visitors but only looks for a change in one direction. A smaller lift or a lower baseline rate needs many more visitors.

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