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Application of Dynamic Programming Method to Marketing Decisions Based on Customer Database

Author

Listed:
  • Zhao Zhongqiu
  • Li Xiaofei
  • Ma Baolong
  • Li Jinlin

    (School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China)

Abstract

The paper focuses on modeling longitudinal customer behavior and develops a dynamic programming (DP) to show how customer transaction database may be used to guide marketing decisions such as pricing and the design of customer reward programs. Dynamic programming is not as a tool to marketing decisions making in this research but rather as a description of consumer behavior. The results show that the method provides a means for evaluating the effectiveness of marketing strategy, for example, customer reward programs. Moreover, the findings from the model estimation indicate that reward program can actually increase the customer’s purchase level and stimulate the repeat purchase behavior.

Suggested Citation

  • Zhao Zhongqiu & Li Xiaofei & Ma Baolong & Li Jinlin, 2016. "Application of Dynamic Programming Method to Marketing Decisions Based on Customer Database," Journal of Systems Science and Information, De Gruyter, vol. 4(2), pages 169-176, April.
    • Handle: RePEc:bpj:jossai:v:4:y:2016:i:2:p:169-176:n:5
    DOI: 10.21078/JSSI-2016-169-08
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    References listed on IDEAS

    as
    1. Dorotic, Matilda & Verhoef, Peter C. & Fok, Dennis & Bijmolt, Tammo H.A., 2014. "Reward redemption effects in a loyalty program when customers choose how much and when to redeem," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 339-355.
    2. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
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