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Markov Decision Processes for Customer Lifetime Value

In: Markov Chains

Author

Listed:
  • Wai-Ki Ching

    (The University of Hong Kong)

  • Ximin Huang

    (Georgia Institute of Technology)

  • Michael K. Ng

    (Hong Kong Baptist University)

  • Tak-Kuen Siu

    (City University London)

Abstract

In this chapter a stochastic dynamic programming model with a Markov chain is proposed to capture customer behavior. The advantage of using Markov chains is that the model can take into account the customers switching between the company and its competitors. Therefore customer relationships can be described in a probabilistic way, see for instance Pfeifer and Carraway [170]. Stochastic dynamic programming is then applied to solve the optimal allocation of the promotion budget for maximizing the Customer Lifetime Value (CLV). The proposed model is then applied to practical data in a computer services company.

Suggested Citation

  • Wai-Ki Ching & Ximin Huang & Michael K. Ng & Tak-Kuen Siu, 2013. "Markov Decision Processes for Customer Lifetime Value," International Series in Operations Research & Management Science, in: Markov Chains, edition 2, chapter 0, pages 107-139, Springer.
    • Handle: RePEc:spr:isochp:978-1-4614-6312-2_5
    DOI: 10.1007/978-1-4614-6312-2_5
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