ABSTRACT In any service system, one of the challenges in assessing customer lifetime value or more is the Classification of customers. Running a successful business is to maintain a good relationship with the customers. Classification of customers (i.e. a company should identify the profitable customers and keep them with an acceptable effort) plays an important role in promotion planning and budget setting. Promotion budget allocation is designed to attract and keep customers. In this thesis we applied stochastic dynamic programming models with the Markov chain techniques for capturing the customer behavior. The model can be implemented using dual simplex method in a Microsoft Excel worksheet, and precise implementation is also demonstrated and discussed in details. Furthermore, a higher-order Markov chain model is a further way of capturing the dynamics of practical data. The practical data from Telecommunication Company is used to illustrate the effectiveness of the higher-order Markov Model thereby observed the improvement in predicting the customer behavior. Keywords: Customer lifetime value, stochastic dynamic programming models, Markov chain, dual simplex method
ABSTRACT In any service system, one of the challenges in assessing customer lifetime value or more is the Classification of customers. Running a successful business is to maintain a good relationship with the customers. Classification of customers (i.e. a company should identify the profitable customers and keep them with an acceptable effort) plays an important role in promotion planning and budget setting. Promotion budget allocation is designed to attract and keep customers. In this thesis we applied stochastic dynamic programming models with the Markov chain techniques for capturing the customer behavior. The model can be implemented using dual simplex method in a Microsoft Excel worksheet, and precise implementation is also demonstrated and discussed in details. Furthermore, a higher-order Markov chain model is a further way of capturing the dynamics of practical data. The practical data from Telecommunication Company is used to illustrate the effectiveness of the higher-order Markov Model thereby observed the improvement in predicting the customer behavior. Keywords: Customer lifetime value, stochastic dynamic programming models, Markov chain, dual simplex method
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