A/B Test Significance Calculator
Find out if your test results are real or just random noise. Two-proportion z-test at 95% confidence level.
Test Your Results
Enter the visitor count and conversions for each variant. We'll tell you if the difference is statistically significant.
A/B Testing Best Practices
Run Tests Long Enough
Wait for at least 1-2 full business cycles (usually 2 weeks minimum). Stopping early inflates false positive rates.
Test One Variable
Change only one element per test — headline, button color, layout. Multi-variable tests need much larger sample sizes.
Sample Size Matters
For a 1% baseline conversion rate, you need roughly 30,000 visitors per variant to detect a 10% relative improvement at 95% confidence.
Don't Peek Too Often
Checking results daily and stopping when you see significance leads to inflated false positives. Set your sample size target upfront.
We run the tests that move the needle.
A/B testing is where small changes turn into big revenue. We design, run, and analyze tests across landing pages, ads, and funnels. 30-minute call, no strings.