Classification of customer lifetime value models using Markov chain
Abstract
A firm’s potential reward in future time from a customer can be determined by customer lifetime value (CLV). There are some mathematic methods to calculate it. One method is using Markov chain stochastic model. Here, a customer is assumed through some states. Transition inter the states follow Markovian properties. If we are given some states for a customer and the relationships inter states, then we can make some Markov models to describe the properties of the customer. As Markov models, CLV is defined as a vector contains CLV for a customer in the first state. In this paper we make a classification of Markov Models to calculate CLV. Start from two states of customer model, we make develop in many states models. The development a model is based on weaknesses in previous model. Some last models can be expected to describe how real characters of customers in a firm.
- Publication:
-
Journal of Physics Conference Series
- Pub Date:
- October 2017
- DOI:
- 10.1088/1742-6596/893/1/012026
- Bibcode:
- 2017JPhCS.893a2026P