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Sample size calculator

Estimate how many visitors you need per variant for an A/B test based on your baseline rate, target uplift, confidence level, power, and traffic.

Test assumptions

What these inputs mean

  • Baseline conversion rate Your current conversion rate before the test starts. If 5 out of every 100 visitors convert, your baseline conversion rate is 5%.
  • Minimum detectable uplift The smallest improvement you care enough to detect. If your baseline is 5% and you enter 10%, the calculator tests for a lift from 5.0% to 5.5%.
  • Confidence level How strict you want to be before calling a result real. A higher confidence level means you need more data, but you reduce the chance of acting on noise.
  • Power How likely the test is to catch a real improvement if that improvement actually exists. Higher power usually means a larger required sample size.
  • Daily visitors across both variants The total traffic you expect to send into the test each day, split across control and variant. This is only used to estimate how long the test may take.