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A/B testing is a method used to compare two versions of a webpage, app, or advertisement to determine which one performs better in achieving a specific goal, such as increasing conversions or engagement. By randomly dividing users into two groups and exposing each group to a different version, marketers can analyze the results based on user behavior and preferences. This technique is heavily reliant on data analytics to make informed decisions that optimize digital advertising strategies and overall media performance.
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