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A-B testing is commonly used in advertising to compare different versions of an ad to determine which performs better. However, traditional A-B tests may not provide clear answers due to a phenomenon called divergent delivery. This occurs when algorithms on platforms like Meta or Google show ads to different groups of users in a way that skews results. For instance, if one ad is shown primarily to users who are generally more responsive to ads, it may seem more effective than another ad simply because of the audience composition rather than inherent ad quality.