Free Tool

Sample Size Calculator

How many visitors do you need per variant before you can trust your A/B test results? Get the exact number — before you start testing.

Sample Size Calculator Per variant
Your current CVR before the test. Check GA4 or your platform.
The smallest relative uplift you care about detecting. e.g. 10% means you want to detect a 3.5% → 3.85% improvement.
Probability of a false positive. 0.05 = 95% confidence.
Probability of detecting a real effect. 80% is standard.

Results will appear here after you click Calculate.

Why sample size matters before you test

The most common A/B testing mistake: stopping a test early because it "looks like" it's winning. Without a pre-calculated sample size, your results are meaningless — you're just watching noise. This is called peeking, and it inflates false positive rates to 25–30%.

Calculate your required sample size before you start. Then commit to running until you hit it — regardless of intermediate results.

Understanding the inputs

Baseline CVR

Your current conversion rate. The lower your CVR, the more traffic you need to detect changes. At 1% CVR you need ~4× more visitors than at 4% CVR.

Minimum Detectable Effect (MDE)

The smallest uplift worth detecting. Setting MDE too low means you need enormous traffic. For most eCommerce tests, 10–20% relative MDE is practical.

Power

At 80% power, if there's a true effect you'll detect it 8 out of 10 times. Higher power = more traffic needed, but fewer missed wins.

Running too many inconclusive tests?

Most brands don't have enough traffic to test everything. We prioritize the highest-impact experiments so every test counts.