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Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability

Author

Listed:
  • Ricardo Montoya

    () (Industrial Engineering Department, University of Chile, Santiago, Chile)

  • Oded Netzer

    () (Marketing Division, Columbia Business School, Columbia University, New York, New York 10027)

  • Kamel Jedidi

    () (Marketing Division, Columbia Business School, Columbia University, New York, New York 10027)

Abstract

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.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:5:p:909-924
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    File URL: http://dx.doi.org/10.1287/mksc.1100.0570
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Asim Ansari & Ricardo Montoya & Oded Netzer, 2012. "Dynamic learning in behavioral games: A hidden Markov mixture of experts approach," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 475-503, December.
    2. Nikolopoulos, Konstantinos & Buxton, Samantha & Khammash, Marwan & Stern, Philip, 2016. "Forecasting branded and generic pharmaceuticals," International Journal of Forecasting, Elsevier, vol. 32(2), pages 344-357.
    3. repec:eee:jouret:v:89:y:2013:i:3:p:231-245 is not listed on IDEAS
    4. repec:eee:ijrema:v:29:y:2012:i:2:p:134-147 is not listed on IDEAS
    5. repec:eee:jouret:v:89:y:2013:i:2:p:140-157 is not listed on IDEAS
    6. repec:eee:joinma:v:36:y:2016:i:c:p:77-90 is not listed on IDEAS
    7. Raghuram Iyengar & Kamel Jedidi, 2012. "A Conjoint Model of Quantity Discounts," Marketing Science, INFORMS, vol. 31(2), pages 334-350, March.
    8. Holtrop, Niels & Wieringa, Jakob & Gijsenberg, Maarten & Stern, P., 2016. "Competitive reactions to personal selling," Research Report 16004-MARK, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    9. repec:eee:jouret:v:89:y:2013:i:4:p:374-396 is not listed on IDEAS
    10. S. Buxton & Kostas Nikolopoulos & M. Khammash & P. Stern, 2015. "Modelling and Forecasting Branded and Generic Pharmaceutical Life Cycles: Assessment of the Number of Dispensed Units," Working Papers 15004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    11. David A. Schweidel & Eric T. Bradlow & Peter S. Fader, 2011. "Portfolio Dynamics for Customers of a Multiservice Provider," Management Science, INFORMS, vol. 57(3), pages 471-486, March.
    12. V. Kumar & S. Sriram & Anita Luo & Pradeep K. Chintagunta, 2011. "Assessing the Effect of Marketing Investments in a Business Marketing Context," Marketing Science, INFORMS, vol. 30(5), pages 924-940, September.

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