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

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  • Sismeiro, Catarina
  • Mizik, Natalie
  • Bucklin, Randolph E.

Abstract

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.

Suggested Citation

  • Sismeiro, Catarina & Mizik, Natalie & Bucklin, Randolph E., 2012. "Modeling coexisting business scenarios with time-series panel data: A dynamics-based segmentation approach," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 134-147.
    • Handle: RePEc:eee:ijrema:v:29:y:2012:i:2:p:134-147
    DOI: 10.1016/j.ijresmar.2011.08.005
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