Free tool · Pre-test planning

A/B test sample size calculator

Don't start a test on a hunch. See exactly how many visitors per variation you need to reach statistical significance, plus how long that takes. Free, instant, no signup.

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Your current conversion rate before testing.

The smallest lift you care about detecting (e.g. 10%). Smaller MDE = much more traffic needed.

Likelihood of finding a winner if one exists. Standard is 80%.

Used to estimate the duration in days.

Why sample size matters

If you stop a test too early, you risk a false positive — thinking a variation is a winner when it's actually random noise. If you run it too long, you waste traffic on a losing variation.

This calculator uses the standard Frequentist formula to determine the fixed-horizon sample size. That means you commit to this number of visitors before you look at the results.

The fixed-horizon problem

Traditional A/B testing is rigid. If you see a winner on day 3, you're technically not allowed to stop until you hit the calculated sample size. That can mean weeks of waiting on a result you already suspect.

Zyro uses sequential testing. This modern approach lets you check results as they come in and stop as soon as a winner is statistically proven, so you spend less traffic finding the answer.

Questions

Sample size, answered.

What is Minimum Detectable Effect (MDE)?

MDE is the smallest improvement (lift) you want to be able to detect. Smaller lifts require much larger sample sizes to prove they aren't random noise.

Why do I need to calculate sample size upfront?

In traditional Frequentist testing, checking results before reaching the sample size increases the false positive rate. This calculator tells you the fixed horizon you must reach for valid results.

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