Find out if your A/B test result is real
Enter the visitors and conversions for each variant and see whether the gap between them is likely real or just noise. A small sample can still return a result that says a difference is significant when it isn't, so check your numbers before you trust the verdict.
Find out whether your A/B test result is real
This calculator takes the number of visitors and conversions from two versions of a headline, subject line or call to action and works out whether the gap between them is large enough to trust or small enough to be down to chance. It's built for anyone running a live copy test who needs to decide whether to keep the new version or go back to the old one. Like any statistical test run on a limited sample, it can point the wrong way, so a narrow result is a reason to keep watching.
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Enter your test numbers
Type in the number of visitors and conversions for each version of your copy.
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Read the significance result
See the confidence level the calculator gives the difference between your two versions.
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Interpret and act on the result
Decide whether the gap is wide enough to back, or whether the test needs more data before you commit.
A/B test significance calculator
Run two versions of a page or an email against each other and you are left with two conversion rates, and a question: is the difference real, or is it what you'd expect from chance alone. This tool takes your visitor and conversion counts for each version and works out a p-value, so you can see how much weight the result will actually bear.
Test Data
Results
Enter your test data and click Calculate to see your results here.
A p-value tells you how likely a result is to be chance. Read it alongside the size of the uplift and how long the test ran before you act on it, and treat the output as a guide, since the calculation can only work with the numbers you give it.
See whether your test result is real
Enter the visitor and conversion numbers for each version you tested and the calculator works out whether the gap between them is large enough to trust or small enough to be chance. It suits anyone comparing two versions of a headline, a subject line or a CTA. A result that reads as significant today can still change if the test keeps running or the traffic mix shifts, so use the answer to decide your next step.
No account needed · free to use · works on any device
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