Free tool
Is that lift real, or is it noise
Enter visitors and conversions for both variants and this runs a two proportion z test, reporting conversion rates, relative lift, and the p value. Significance at ninety five percent means the difference is unlikely to be noise. It does not mean the difference is large enough to be worth shipping.
Last reviewed 27 August 2026
Result
Conversion rate, A
5.00%
250 of 5,000
Conversion rate, B
5.80%
290 of 5,000
Relative lift
+16.0%
Absolute difference 0.80%
p value, two tailed
0.0768
z of 1.770 against a threshold of 0.05
The two variants
| Variant | Visitors | Conversions | Rate |
|---|---|---|---|
| A | 5,000 | 250 | 5.00% |
| B | 5,000 | 290 | 5.80% |
This does not reach 95 percent confidence. A p value of 0.0768 means a difference this large would turn up reasonably often even if the two variants were identical. Either keep running or accept that you cannot separate them.
How this works
What the numbers mean.
- 01Both variants are treated as proportions. The test pools them into a single rate, computes the standard error of the difference under the assumption that the two are the same, and expresses the observed gap as a z score in standard errors.
- 02The p value is the two tailed area beyond that z score in a standard normal distribution. It is computed here with the Abramowitz and Stegun 7.1.26 approximation to the error function, which is accurate to about seven decimal places.
- 03The confidence interval uses the unpooled standard error, because once you accept the variants differ, pooling them is no longer the right assumption.
Assumptions and limits
- Statistical significance is not practical significance. A tiny lift can be significant with enough traffic and still not be worth the work of shipping it.
- Checking results before the planned sample size is reached inflates false positives badly. Every look at the data is another chance to see noise that happens to cross the threshold.
- This assumes visitors were split randomly and independently, and that you decided what to measure before you started. Picking the winning metric afterwards makes the p value meaningless.
Questions about this tool
What does a p value of 0.05 actually mean?
Why is peeking at results a problem?
My result is significant but the lift is tiny. Should I ship it?
Is a two tailed test right for my case?
What if I am comparing more than two variants?
This tool is free and there is nothing to sign up for. If you would rather have the work done than calculate it, that is what Zway does.