Portfolio Dynamics for Customers of a Multiservice Provider
Multiservice providers, such as telecommunication and financial service companies, can benefit from understanding how customers' service portfolios evolve over the course of their relationships. This can provide guidance for managerial issues such as customer valuation and predicting customers' future behavior, whether it is acquiring additional services, selectively dropping current services, or ending the relationship entirely. In this research, we develop a dynamic hidden Markov model to identify latent states that govern customers' affinity for the available services through which customers evolve. In addition, we incorporate and demonstrate the importance of separating two other sources of dynamics: portfolio inertia and service stickiness. We then examine the relationship between state membership and managerially relevant metrics, including customers' propensities for acquiring additional services or terminating the relationship, and customer lifetime value. Through a series of illustrative vignettes, we show that customers who have discarded a particular service may have an increased risk of canceling all services in the near future (as intuition would suggest) but also may be more prone to acquire more services, a provocative finding of interest to service providers. Our findings also emphasize the need to look beyond the previous period, as in much current research, and consider how customers have evolved over their entire relationship in order to predict their future actions. This paper was accepted by Pradeep Chintagunta, marketing.
Volume (Year): 57 (2011)
Issue (Month): 3 (March)
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- Cooper, Lee G & Nakanishi, Masao, 1983. " Standardizing Variables in Multiplicative Choice Models," Journal of Consumer Research, Oxford University Press, vol. 10(1), pages 96-108, June.
- Seetharaman, P B & Chintagunta, Pradeep K, 2003. "The Proportional Hazard Model for Purchase Timing: A Comparison of Alternative Specifications," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 368-82, July.
- Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
- Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics, Springer, vol. 5(2), pages 163-190, June.
- Peter S. Fader & Bruce G. S. Hardie, 2010. "Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity," Marketing Science, INFORMS, vol. 29(1), pages 85-93, 01-02.
- David A. Schweidel & Peter S. Fader & Eric T. Bradlow, 2008. "A Bivariate Timing Model of Customer Acquisition and Retention," Marketing Science, INFORMS, vol. 27(5), pages 829-843, 09-10.
- Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
- Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
- Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
- Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
- Rakesh Niraj & V. Padmanabhan & P. B. Seetharaman, 2008. "Research Note—A Cross-Category Model of Households' Incidence and Quantity Decisions," Marketing Science, INFORMS, vol. 27(2), pages 225-235, 03-04.
- David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
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