Predicting Customer Churn Using CLV in Insurance Industry

Subject Areas : Business Strategy

Vahid Dust Mohammadi ¹ (Department of Industrial Engineering, Tarbit Modares University, Tehran, Iran)
Amir Albadvi ² (Department of Industrial Engineering, Tarbit Modares University, Tehran, Iran)
Babak Teymorpur ³ (Department of Industrial Engineering, Tarbit Modares University, Tehran, Iran)

Received: 2015-01-31 Accepted : 2015-03-01 Published : 2016-01-01

Keywords:

References:

[1] Berry, M. J. and Linoff, G. S. (2004), Data mining techniques: for marketing,

sales, and customer relationship management: John Wiley & Sons.

[2] Turban, E., Sharda, R., Delen, D., and Efraim, T. (2007), Decision support

and business intelligence systems: Pearson Education India.

[3] Tsai, C. F. and Lu, Y. H. (2009), “Customer churn prediction by hybrid

neural networks,” Expert Systems with Applications, vol. 36, pp. 12547-

12553.

[4] Ling, R. and Yen, D. C. (2001), “Customer relationship management: An

analysis framework and implementation strategies,” Journal of Computer

Information Systems, vol. 41, pp. 82-97.

[5] KhakAbi, S., Gholamian, M. R., and Namvar, M. (2010), “Data mining

applications in customer churn management,” in Intelligent Systems,

Modelling and Simulation (ISMS), International Conference on, pp. 220-

225.

[6] Zhang, Y., Liang, R., Li, Y., Zheng, Y., and Berry, M. (2011), “Behavior-

Based Telecommunication Churn Prediction with Neural Network Approach,”

in Computer Science and Society (ISCCS), International Symposium

on, pp. 307-310.

[7] Benoit, D. F. and Van den Poel, D. (2012), “Improving customer retention

in financial services using kinship network information,” Expert Systems

with Applications, vol. 39, pp. 11435-11442.

[8] Kracklauer, A., Mills, H. D. Q., and Seifert, D. (2004), “Customer

management as the origin of collaborative customer relationship management,”

in Collaborative Customer Relationship Management, Ed:

Springer, pp. 3-6.

[9] Kajvary, (2013), “important factors in brand equity in insurance industry

in customer perspective,” insurance journal.

[10] Chu, B. H., Tsai, M. S., and Ho, C. S. (2007), “Toward a hybrid data

mining model for customer retention,” Knowledge-Based Systems, vol.

20, pp. 703-718.

 [11] Kim, H. S. and Yoon, C. H. (2004), “Determinants of subscriber churn

and customer loyalty in the Korean mobile telephony market,” Telecommunications

Policy, vol. 28, pp. 751-765.

[12] Bahman, A. (2014), “modeling CLV in insurane industry,” engineering,

tarbiat modares, Iran.

[13] Malthouse, E. C. and Blattberg, R. C. (2005), “Can we predict customer

lifetime value?” Journal of Interactive Marketing, vol. 19, pp. 2-16.

[14] Amin, R. (2011), “using predicted improvement factors for communication

creteria in binary logistic,” operation management.