Customer migration, campaign budgeting, revenue estimation: the elasticity of Markov Decision Process on customer lifetime value

Abstract

To predict the profitability of a customer, today’s firms have to practice Customer Lifetime Value (CLV) computation. Different approaches are proposed in the last ten years to analyze the complex customer phenomenon. One of them is Markov Decision Process (MDP) model. The class of Markov Models is an effective and a flexibility decision model. Whereas the use of MDP model is limited by its assumption, in this paper, we attempt to introduce an extension model for MDP: Higher-order Markov Decision Model (HMDP). HMDP can perform excellently in CLV calculation and overcome the limitation of MDP. By using a real application, we will demonstrate how it can be used efficiently in a firm’s daily operations.

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Cite this paper

@inproceedings{Ching2004CustomerMC, title={Customer migration, campaign budgeting, revenue estimation: the elasticity of Markov Decision Process on customer lifetime value}, author={Wai-Ki Ching and Michael K. Ng}, year={2004} }