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Abstract

Described herein are example systems and operations for enhancing targeted advertising using A/B testing. These examples provide solutions to problems in targeted advertising, such as the problem of not being able to identify audience and/or situational targets mostly or only influenced by the ad or ad campaign of concern. For example, described herein are solutions that can build a pair of differential behavioral data sets similar to an A/B clinical study. Then two or more models can be generated on each data set. In an example, these models can be based on machine learning and/or statistical analysis. The differential learning between the two or more models can then be used to enhance predictions of desired response probabilities mostly or only due to the influence of the ad or ad campaign being modeled.

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