Using Markov decision analysis to analyze retention of patients who have chronic disease prescriptions

One characteristic of service is in its lower barrier to entry. Fierce competition is almost a norm among many service businesses. The key to successful customer relationship management embeds in the ability to acquire the customer, to retain the customer and make frequent customers. This research suggests a probabilistic analytic framework to firstly create the transition matrices for acquiring customer, for retaining customer, and for migrating customer; it is ensued by incorporating Markov decision process to find a set of policies that can optimize the revenues and/or profits and assist in better decision-making. A case study of a drug store chain which is currently trying to start and retain the relationship with the patients who have chronic disease prescriptions is carried out; Empirical results and analysis based on the framework will be used to test the effectiveness of the proposed framework.