A/B Test Duration Calculator
Calculate how long your A/B test needs to run to reach statistical significance with reliable results.
Formula
What is A/B Testing?
A/B testing (also called split testing) is a method of comparing two versions of a webpage, email, or ad to determine which one performs better. You split your traffic between version A (control) and version B (variant), then measure which version generates more conversions.
For e-commerce, A/B tests are used to optimize product pages, checkout flows, CTAs, pricing, headlines, images, and email subject lines — any element that affects revenue.
Why Test Duration Matters
Running an A/B test for too short a period leads to false positives — you might declare a winner that isn't actually better. Running too long wastes time and traffic. This calculator uses statistical formulas to determine the exact sample size and duration needed.
- Statistical significance: 95% is the industry standard — meaning there's only a 5% chance the result is due to random chance
- Statistical power: 80% is standard — meaning an 80% chance of detecting a real difference if one exists
- Minimum Detectable Effect (MDE): The smallest improvement you want to detect. Smaller effects need larger samples
A/B Testing Best Practices for E-commerce
- Test one thing at a time: Change only one element per test for clear results
- Run tests for full weeks: Shopping behavior varies by day — always run for at least 1-2 full business cycles
- Never peek and stop early: Wait for the calculated duration even if results look clear
- Document everything: Track hypothesis, screenshots, results, and learnings
- Prioritize high-impact pages: Homepage, product pages, cart, and checkout first