Presenting a Model for Calculating ISACO Customers Lifetime Value by Markov Chain Using Data Mining Techniques

One of the key issues in studies on customer relationship management (crm) and marketing budget allocation is to calculate the customer’s lifetime value and apply it to macro-management decisions. a major challenge in this issue is considering the possibility of changes in the behavior of customers with the turn of time in the model. in this study, a new approach has been used to estimate the parameters of the model proposed for calculating the future lifetime value of iran khodro spare parts and after- sale services co. (isaco) customers. this method takes into consideration the possibility of changes in customer behavior throughout their interaction with the company. in this article, the customers of isaco are first classified using clustering techniques and use multilayer neural network to calculate the monetary value of each group of customers during a specific period of time. then, the markov chain approach is used to develop a model for calculating the lifetime value of isaco’s customers considering the possibility of changes in their behavior in different periods. the results obtained here can be used in the allocation of marketing budget and adoption of macro-management decisions to envisage various projects for customers with different lifetime values