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

Catarina Sismeiro, Natalie Mizik and Randolph E. Bucklin

International Journal of Research in Marketing, 2012, vol. 29, issue 2, 134-147

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.

Keywords: Sales force; Segmentation; Marketing-mix effectiveness; Econometric methods; Time-series modeling (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijrema:v:29:y:2012:i:2:p:134-147

DOI: 10.1016/j.ijresmar.2011.08.005

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