Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability
The U.S. pharmaceutical industry spent upwards of $18 billion on marketing drugs in 2005; detailing and drug sampling activities accounted for the bulk of this spending. To stay competitive, pharmaceutical managers need to maximize the return on these marketing investments by determining which physicians to target as well as when and how to target them. In this paper, we present a two-stage approach for dynamically allocating detailing and sampling activities across physicians to maximize long-run profitability. In the first stage, we estimate a hierarchical Bayesian, nonhomogeneous hidden Markov model to assess the short- and long-term effects of pharmaceutical marketing activities. The model captures physicians' heterogeneity and dynamics in prescription behavior. In the second stage, we formulate a partially observable Markov decision process that integrates over the posterior distribution of the hidden Markov model parameters to derive a dynamic marketing resource allocation policy across physicians. We apply the proposed approach in the context of a new drug introduction by a major pharmaceutical firm. We identify three prescription-behavior states, a high degree of physicians' dynamics, and substantial long-term effects for detailing and sampling. We find that detailing is most effective as an acquisition tool, whereas sampling is most effective as a retention tool. The optimization results suggest that the firm could increase its profits substantially while decreasing its marketing spending. Our suggested framework provides important implications for dynamically managing customers and maximizing long-run profitability.
Volume (Year): 29 (2010)
Issue (Month): 5 (09-10)
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- Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
- Michael Lewis, 2005. "Research Note: A Dynamic Programming Approach to Customer Relationship Pricing," Management Science, INFORMS, vol. 51(6), pages 986-994, June.
- George E. Monahan, 1982. "State of the Art---A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms," Management Science, INFORMS, vol. 28(1), pages 1-16, January.
- Harikesh Nair, 2007.
"Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games,"
Quantitative Marketing and Economics (QME),
Springer, vol. 5(3), pages 239-292, September.
- Nair, Harikesh S., 2006. "Intertemporal Price Discrimination with Forward-Looking Consumers: Application to the US Market for Console Video-Games," Research Papers 1947, Stanford University, Graduate School of Business.
- Ramkumar Janakiraman & Shantanu Dutta & Catarina Sismeiro & Philip Stern, 2008. "Physicians' Persistence and Its Implications for Their Response to Promotion of Prescription Drugs," Management Science, INFORMS, vol. 54(6), pages 1080-1093, June.
- Puneet Manchanda & Pradeep K. Chintagunta, 2004. "Responsiveness of Physician Prescription Behavior to Salesforce Effort: An Individual Level Analysis," Marketing Letters, Springer, vol. 15(2_3), pages 129-145, 07.
- 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.
- John Liechty & Rik Pieters & Michel Wedel, 2003. "Global and local covert visual attention: Evidence from a bayesian hidden markov model," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 519-541, December.
- Erdem, Tulin & Sun, Baohong, 2001. "Testing for Choice Dynamics in Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 142-152, April.
- Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
- 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.
- Yossi Aviv & Amit Pazgal, 2005. "A Partially Observed Markov Decision Process for Dynamic Pricing," Management Science, INFORMS, vol. 51(9), pages 1400-1416, September.
- Prasad A. Naik & Kalyan Raman & Russell S. Winer, 2005. "Planning Marketing-Mix Strategies in the Presence of Interaction Effects," Marketing Science, INFORMS, vol. 24(1), pages 25-34, June.
- Günter J. Hitsch, 2006. "An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty," Marketing Science, INFORMS, vol. 25(1), pages 25-50, 01-02.
- Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
- Shie Mannor & Duncan Simester & Peng Sun & John N. Tsitsiklis, 2007. "Bias and Variance Approximation in Value Function Estimates," Management Science, INFORMS, vol. 53(2), pages 308-322, February.
- Sridhar Narayanan & Puneet Manchanda, 2009. "Heterogeneous Learning and the Targeting of Marketing Communication for New Products," Marketing Science, INFORMS, vol. 28(3), pages 424-441, 05-06.
- Duncan I. Simester & Peng Sun & John N. Tsitsiklis, 2006. "Dynamic Catalog Mailing Policies," Management Science, INFORMS, vol. 52(5), pages 683-696, May.
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