For A/B testing to be effective, you need to ensure that the difference between the two versions is statistically significant.
Use this A/B Test Calculator to determine if the difference is large enough to be meaningful, based on your audience size and results.
The calculator will indicate if the result is statistically significant.
Conversion Rate:
The conversion rate is the percentage of visitors who take a desired action, such as making a purchase, signing up for a newsletter, or clicking on a link. It's calculated by dividing the number of conversions by the total number of visitors and multiplying by 100.
Z-Score:
The Z-Score tells you how many standard deviations an outcome is from the average. In A/B testing, it helps you see how different two groups (A and B) are. A higher Z-Score means a bigger difference between the two versions.
P-Value:
The P-Value tells you the probability that the results happened by chance. In A/B testing, a P-Value below 0.05 usually means the difference between version A and version B is statistically significant and not just random.
Statistically Significant
For a result to be considered statistically significant, we typically look for a confidence level of 95% or higher. This means we can be 95% sure that the difference in results between A and B is not due to random chance.
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