Interactive tool

See whether your A/B test result is real

Enter the visitors and conversions for two versions of a page, and this calculator works out whether the difference between them is large enough to trust, or still likely down to chance.

How-To Guide

A/B Test Significance Calculator: find out if your result is real or just noise

Running two versions of a page or an email and watching one pull ahead feels like progress. This calculator takes the numbers from both versions of a test and works out how likely it is that the gap you saw would show up even if neither version was actually better. It's built for anyone comparing two headlines, two subject lines or two landing pages who wants to know whether to trust a result before changing anything on the strength of it.

Level: Beginner
Best for: Site owners and freelancers testing a headline, subject line or landing page
Diagram comparing two test versions with their conversion counts and a significance result
  1. Enter your test numbers

    Enter the number of visitors or emails each version reached and how many converted, clicked or signed up.

  2. Check the significance result

    Read the result to see whether the gap between your two versions is large enough, given the numbers involved, to be more than chance.

  3. Decide what to do next

    Weigh the result against your sample size and how long the test ran before deciding to keep, extend or drop the change.

A/B test significance calculator

Enter the visitor and conversion numbers from your two versions and this tool works out the p-value, telling you how likely it is that the difference between them is real. It's built for anyone running a test on a landing page, email subject line or checkout flow who wants a clear answer before deciding which version to keep.

Test Data

Control
Conversion rate: —
Variant
Conversion rate: —
Confidence level
Test type

Results

Enter your test data and click Calculate to see your results here.

Control
0%
Variant
0%
P-value
—
Lower is more significant
Relative uplift
—
Variant vs control

A result can be statistically significant and still too small to matter for your business, so weigh the p-value alongside the size of the uplift and what it would actually take to act on it. This tool can give you a misleading answer if your sample is small or your test ran for too short a time, so treat the output as a steer.

Free Tools

See whether your test result is real, or just noise

An A/B test tells you which version of a page or email did better, but not whether the gap between them is big enough to trust. This calculator takes the visitor and conversion counts from each version and works out whether the difference holds up statistically, or whether it could just as easily be chance. It's built for a landing page or subject line test with a modest number of visitors. A result that looks promising with too few visitors is still a guess.

No sign-up needed · Free to use · Works on any device