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Determine whether your marketing A/B test campaign results represent a statistically reliable lift or just random chance.
Significance Calculations
Control CR (A)
4.00%
Challenger CR (B)
5.00%
Conversion Lift
+25.00%
Calculated p-value:
0.0135
How A/B Test Significance Works
A/B testing calculators use a two-proportion Z-hypothesis test to confirm whether the challenger's conversion rate difference is statistically significant.
Key Terms:
- Conversion Lift: The percentage improvement (or decrease) of challenger B relative to control A.
- p-value: The probability that the observed conversion difference happened by random noise. A smaller p-value implies a more reliable result.
- Confidence Level: Usually set to 95%. If confidence level is ≥ 95% (meaning p-value ≤ 0.05), the test result is considered statistically significant.
Never conclude an A/B test too early. Make sure you collect a representative sample size (typically at least 100 conversions per variation) and run the test for a full week to avoid weekend/weekday traffic bias.