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A method of comparing two versions of a webpage, email, or ad to determine which performs better based on a specific metric.
A/B testing (also called split testing) randomly shows different versions to different users and measures which version achieves a higher conversion rate, click-through rate, or other target metric. It's used to optimize headlines, CTAs, layouts, images, pricing displays, email subject lines, and ad copy. Statistical significance is required to draw valid conclusions.
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