Coarse Personalization
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Advances in heterogeneous treatment effects estimation enable firms to personalize marketing mix elements and target individuals at an unmatched level of granularity, but feasibility constraints limit such personalization. In practice, firms choose which unique treatments to offer and which individuals to assign to each treatment to maximize profits, and we denote the firm's problem as the coarse personalization problem. We solve the coarse personalization problem using a two-step procedure that forms segmentation and targeting decisions in concert. First, the firm personalizes by estimating conditional average treatment effects. Second, the firm discretizes by utilizing treatment effects to choose which unique treatments to offer and who to assign to these treatments. The second step is the main contribution of our paper and is a novel application of optimal transport methods. We adapt Lloyd's Algorithm to computationally solve the second step. With data from a large-scale field experiment for promotions management, we find that our methodology outperforms classical marketing techniques that segment on consumer characteristics or preferences. Using our procedure, the firm recoups over 99.5 while offering only five unique treatments. We conclude by discussing how coarse personalization arises in other marketing areas.
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