Modeling coexisting business scenarios with time-series panel data: A dynamics-based segmentation approach

At a given point in time, individual consumers may be in different stages of the product adoption or consumption cycle. As a result, different types of behavioral patterns may coexist within a single product market. Existing segmentation approaches typically do not address long-term dynamics in customer response and do not adequately capture this phenomenon. We develop an approach for modeling the coexistence of multiple dynamic behavioral patterns (business scenarios) within a single product market. We apply this approach to physician panel data on drug prescriptions and direct-to-physician promotions. We find markedly different responses across physician segments. For firms that track customer-level marketing activity and sales over time, market segmentation based on dynamic scenarios can provide a new tool for efficient targeting. The proposed approach is straightforward to implement and is scalable to very large samples and continuous testing.

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