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Conversion
A/B Testing
A/B testing is a controlled experiment that splits traffic between two versions of a page, ad, email, or flow to measure which drives more of a target action. The result is only trustworthy once it reaches statistical significance — typically a 95% confidence level on a pre-calculated sample size — so the lift is attributable to the change rather than to chance. Calling a winner early is the most common mistake; by one analysis, most winning tests would not have held up if run to their proper sample size. It is the core mechanic of disciplined conversion work, not a one-off.
Source: convert.com
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