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A/B Test Significance Calculator

The A/B Test Significance Calculator tells you whether the difference between two variants is real or could be random chance. Enter visitors and conversions for each version and it runs a two-proportion z-test, returning confidence level, uplift and p-value in real time, with a plain-English verdict.

  • 100% free
  • No sign-up
  • Runs in your browser
Variant A Control
Conv. Rate: 0%
Variant B Challenger
Conv. Rate: 0%

Waiting for Data...

Enter your test data above to see if your results are statistically significant.

0% Confidence Level
0% Observed Uplift
- P-Value

How it works

How to use the A/B Test Significance Calculator

  1. Enter control data

    Add visitors and conversions for Variant A, your original.

  2. Enter variant data

    Add visitors and conversions for Variant B.

  3. Read the verdict

    A clear winner or loser needs 95% confidence or more. Between 80% and 95% means keep testing.

  4. Decide

    Roll out a significant winner, or keep the test running until you have enough data.

Why significance testing matters

Conversion rates bounce around naturally. Run the same page as A and B and one will "win" by chance. Without a significance test, teams regularly declare winners off a handful of extra conversions, roll out changes that do nothing, and wonder why the promised uplift never appears.

How to run a trustworthy test

  1. Decide your sample size in advance based on your baseline rate and the smallest uplift worth detecting.
  2. Run for full weeks. Behaviour differs between weekdays and weekends, so cover at least one and ideally two full cycles.
  3. Do not stop the moment you hit 95%. Repeatedly checking and stopping early inflates false positives.
  4. Test one meaningful change at a time, so you know what caused the result.
  5. Check segments such as mobile and desktop before rolling out, in case a winner overall loses for a key audience.

What to test first

Focus on changes big enough to matter: the headline and offer, the call to action, form length, social proof and page layout above the fold. For paid search, testing landing pages alongside ad copy often delivers the biggest gains, because improving conversion rate lowers your effective cost per lead.

Questions

A/B Test Significance Calculator FAQs

What does statistical significance mean?

It means the difference you observed is unlikely to be explained by random variation. At 95% confidence, a difference this large would occur by chance only about 5% of the time if the variants were genuinely the same.

What is a p-value?

The probability of seeing a difference at least this large if there were truly no difference. The calculator shows confidence as 1 minus the p-value.

Which test does it use?

A two-proportion z-test with a pooled proportion, the standard method for comparing two conversion rates.

How much traffic do I need?

It depends on your baseline conversion rate and the size of the effect. Be wary of calling winners on a few hundred visitors per variant, even if confidence briefly crosses 95%.

Is my data uploaded?

No. Calculations run in your browser.

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