Calculate A/B test sample size and statistical significance. Enter conversion rates and traffic to determine how long to run your experiment.
Enter your baseline conversion rate, minimum detectable effect, statistical significance level, and statistical power to calculate the required sample size per variation. Also check if your completed test results are statistically significant.
Run the test until you reach the calculated sample size for both variations. This depends on your traffic volume, baseline conversion rate, and the minimum effect size you want to detect.
Statistical significance (usually 95%) means there is less than a 5% probability that the observed difference between variations is due to random chance rather than a real effect.
MDE is the smallest improvement you want to be able to detect. A smaller MDE requires a larger sample size. For example, detecting a 1% lift requires more traffic than detecting a 10% lift.
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