Abstract
This study provides a stochastic dynamic programming model with a Markov chain that explicitly focuses on the customer as well as a new model for valuing the customers in the banking industry. The proposed framework calculates individual customer’s lifetime value dynamically. The study follows a stochastic dynamic programming model that is based on the Markov chain. The deduced findings are illustrated with supplementary context from an outstanding case study. The findings underline the importance of the stochastic model for calculating customer lifetime value based on customer behavior. The presented framework provides a beneficial way for future research and valuable insight for allocating promotional marketing strategies to customer groups. The presented framework provides a dynamic model for calculating the individual customer’s lifetime value. The main contribution of the study is the explicit calculation of individual customer’s lifetime value in the banking industry. Thus, this study provides a stochastic framework for customer segmentation and allocates appropriate marketing promotion strategies. Furthermore, the results of this study were supported by real customer data of one of the largest banks in the MENA region.
Original language | English |
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Journal | Industrial Engineering and Management Systems |
Volume | 19 |
Issue number | 4 |
Pages (from-to) | 744-757 |
Number of pages | 14 |
ISSN | 1598-7248 |
DOIs | |
Publication status | Published - Dec 2020 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 KIIE
Keywords
- Bank
- Customer Lifetime Value
- Customer Profitability
- Markov Chain Model