An underpowered test cannot distinguish a real effect from none, so a null result from one carries almost no information.
Work out the smallest effect your actual sample could have detected. If that number is a 25% lift, then a null result has ruled out nothing anybody hoped for — almost no real change moves a conversion rate that far. The test did not show the change does not work; it showed the test could not see whether it did, which is a different sentence with a different conclusion.
A null result from a well-powered test is genuinely informative, and treating every null as an artefact is the opposite error. If the test could reliably have caught a 3% lift and did not, that is real evidence the effect is small — which is often exactly what you needed to know.
Estimate with the rule, then check it against the calculator that models it properly.
Open A/B Test & Sample Size →An underpowered test cannot distinguish a real effect from none, so a null result from one carries almost no information. Work out the smallest effect your actual sample could have detected.