A/B Test Significance Calculator
Calculate if your email A/B test results are statistically significant. Enter your sample sizes and conversion rates to know if you can trust your test results or need more data.
Determine if your test results are statistically significant
AControl Variation
BTest Variation
Understanding the results
- 95% confidence means 5% chance results are due to random chance
- P-value < 0.05 indicates statistical significance
- Z-score measures standard deviations from the mean
- Larger sample sizes give more reliable results
- Don't end tests early - wait for significance
About this tool
Not all improvements are real—randomness can make weaker options look better by chance. This calculator tells you if your test results are statistically significant before you make major decisions. Before running tests, optimize your subject lines and preheaders for baseline improvement. Track results with our UTM parameter builder and analyze overall campaign performance with our email calculator to contextualize your test wins.
Frequently Asked Questions
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