Definition
Confidence Interval
A range of values that likely contains the true result of an A/B test. A 95% confidence interval means there's a 95% probability the true value falls within the range.
What does Confidence Interval mean?
A confidence interval is a range of values, calculated from test data, that is likely to contain the true underlying conversion rate or effect size for a given confidence level, most commonly 95%. It expresses the uncertainty inherent in measuring a sample rather than the entire population of possible visitors.
Why does Confidence Interval matter?
It matters in testing because a single point estimate, like 'variant B converted 8% better,' can be misleading with limited data; the confidence interval shows whether that 8% could plausibly be anywhere from a small loss to a large gain, which changes how much weight a team should put on the result.
How is Confidence Interval applied in practice?
Confidence intervals are calculated automatically by A/B testing calculators and platforms from sample size, conversion counts, and variance, and teams use them to decide whether to keep running a test, call a winner, or conclude the difference between variants is not yet distinguishable from chance.
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Where this fits
Confidence Interval sits in the conversion analytics part of the NotiProof resource network.
Read the Conversion Analytics guide