A/B test sample size calculator
Work out how many visitors each version of your A/B test needs, from your conversion rate and the smallest lift you care about. Free, no signup.
How it works
The calculator uses the standard formula for comparing two conversion rates:
n = (z₁₋α/₂ × √(2p̄(1 − p̄)) + z₁₋β × √(p₁(1 − p₁) + p₂(1 − p₂)))² ÷ (p₂ − p₁)²
where p₁ is your current conversion rate, p₂ is the rate after the lift you want to detect, p̄ is their average, and the z values come from your confidence level and power.
Example: a 3% signup rate and a 20% lift (3% to 3.6%) at 95% confidence and 80% power needs about 13,900 visitors per version, so about 27,800 in total. Halve the lift you want to detect and you need roughly four times as many visitors. That's why small sites should test bold changes.
Questions people ask
What sample size do I need for an A/B test?+
It depends on your conversion rate and the smallest lift you want to detect. At a 3% conversion rate, detecting a 20% relative lift at 95% confidence and 80% power takes about 13,900 visitors per version. Detecting a 10% lift takes about 53,000.
What is statistical power?+
Power is the chance your test detects a real lift of the size you chose. At 80% power, one in five real lifts of that size will be missed. Raising power to 90% needs about a third more visitors.
Should I use relative or absolute lift?+
This calculator uses relative lift, the way most people talk about results: going from 3% to 3.6% is a 20% relative lift and a 0.6 point absolute lift.
Does sample size change if I test on revenue instead of conversions?+
Yes. Revenue per visitor varies more than a yes or no conversion, because order values differ, so revenue tests usually need more visitors. Outtest accounts for that spread when it calls a winner.
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