Browse > Article
http://dx.doi.org/10.7469/JKSQM.2014.42.2.221

Development of Prediction Model for Churn Agents -Comparing Prediction Accuracy Between Pattern Model and Matrix Model-  

An, Bong-Rak (Department of Management, Graduate School, Kyung Hee University)
Lee, Sae-Bom (Department of Management, Graduate School, Kyung Hee University)
Roh, In-Sung (School of Management, Kyung Hee University)
Suh, Yung-Ho (School of Management, Kyung Hee University)
Publication Information
Journal of Korean Society for Quality Management / v.42, no.2, 2014 , pp. 221-234 More about this Journal
Abstract
Purpose: The Purpose of this study is to develop a model for predicting agent churn group in the cosmetics industry. We develope two models, pattern model and matrix model, which are compared regarding the prediction accuracy of churn agents. Finally, we try to conclude if there is statistically significant difference between two models by empirical study. Methods: We develop two models using the part of RFM(Recency, Frequency, Monetary) method which is one of customer segmentation method in traditional CRM study. In order to ensure which model can predict churn agents more precisely between two models, we used CRM data of cosmetics company A in China. Results: Pattern model and matrix model have been developed. we find out that there is statistically significant differences between two models regarding the prediction accuracy. Conclusion: Pattern model and matrix model predict churn agents. Although pattern model employed the trend of monetary mount for six months, matrix model that used the amount of sales per month and the duration of the employment is better than pattern model in prediction accuracy.
Keywords
CRM; Customer; Churn; RFM; Agent; Pattern; Matrix; Model;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Kim, Su-Yeon, Jung, Tae-Soo, Suh, Eui-Ho, and Hwang, Hyun-Seok. 2006. "Customer segmentation and strategy development based on customer lifetime value: A case study." Expert Systems with Applications 31:101-107.   DOI   ScienceOn
2 Kincaid, J. W. 2003. "Customer Relationship Management: Getting it Right!." New Jersey: Prentice-Hall PTR.
3 Moe, Wendy w., and Peter, S. Fader. 2001. "Uncovering Patterns in Cybershopping." California Management Review 43(4):106-117.
4 Paravtiyar, A., and Sheth, Jagdish N. 2001, "Customer Relationship Management: Emerging Practice, Process, and Discipline." Journal of Economic and Social Research 3(2):1-34.
5 Scott, A. Neslin, Sunil, Gupta, Wagner, Kamakura, Junxiang, Lu, and Charlotte, H. 2006. "Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models." Journal of Marketing Research 43(2):204-211.   DOI   ScienceOn
6 Shani, D., and Chalasani, S. 1992. "Exploiting Niches Using Relationship Marketing." Journal of Consumer Marketing 9(3):33-42.   DOI
7 Hosseini, S. M. S. et al. 2010. "Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty." Expert Systems with Applications 37:5259-5264.   DOI   ScienceOn
8 Vavra, Terry G. 1992. "How to Keep Customers for life through relationship marketing." Homewood: Busienss one Irwin.
9 Ha, S. H., Bae, S. M., and Park, S. C. 2002. "Customer's time-variant purchase behavior and corresponding marketing strategies: an online retailer's case." Computers & Industrial Engineering 43(4):801-820.   DOI   ScienceOn
10 Fader, P. S., Hardie, B. G. S., and Lee, K. L. 2005. "Counting your customers, The easy way: An alternative to the Pareto/NBD model." Marketing Science 24(2):275-284.   DOI   ScienceOn
11 Shin, Geoncheol, Ku, Yeongae, and Choi, sunghwan. "The Study on the Influence of Consumers' Value that Affects Brand Charisma, Brand Attitude and Purchase Intention With Relevance to Masstige Brand." Journal of Korean Society for Quality Management 39(4).
12 Hsieh, N. C. 2004. "An integrated data mining and behavioral scoring model for analyzing bank customer." Expert Systems with Applications 27:623-633.   DOI   ScienceOn
13 Hung, S. Y., Yen, D. C., and Wang, H. Y. 2006. "Applying data mining to telecom churn management." Expert Systems with Applications 31:515-524.   DOI   ScienceOn
14 Hwang, Hyunseok, Jung, Taesoo, and Suh, Euiho. 2004. "An LTV model and customer segmentation based on customer value: A case study on the wireless telecommunication industry." Expert Systems with Applications 26:181-188.   DOI   ScienceOn
15 Kim, Hyun-Mo et al. 2012. "Variables Affecting End-User Satisfaction in Application Market." Journal of Korean Society for Quality Management 40(2).
16 John, H., Ashutosh, T., Rajkumar, R., and Dymitr, R. 2008. "Churn Prediction: Does Technology Matter?." World Academy of Science, Engineering and Technology 16.
17 Kaymak, U. 2001. "Fuzzy target selection using RFM variables." Proceedings of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference, 1038-1043.
18 Abbott, J. 2001. "Data data everywhere and not a byte of use?." Qualitative Market Research 4(3):182-192.   DOI   ScienceOn
19 Berry, L. L. 1995. "Relationship Marketing of services-Growing Interest, Emerging Perspectives." Journal of the Academy of Marketing Science:236-245.
20 Adrian, Payne, and Pennie, Frow. 2005. "A Strategic Framework for Customer Relationship Management." Journal of Marketing 69(4):167-176.   DOI   ScienceOn
21 Bult, J. R., and Wansbeek, T. 1995. "Optimal Seleciton for Direct Mail." Market Sci 14(4):378-394.   DOI   ScienceOn
22 Yeh, C., Yang, K., and Ting, T. 2009. "Knowledge discovery on RFM model using Bernoulli sequence." Expert Systems with Applications 36:5866-5871.   DOI   ScienceOn
23 Verhoef, Peter C. 2003. "Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development." Journal of Marketing 67(4):30-45.   DOI   ScienceOn
24 Wei, C. P., and Chiu, I. T. 2002. "Turning telecommunications call details to churn prediction: A data mining approach." Expert Systems with Applications 23:103-112.   DOI   ScienceOn
25 Winer, R. S. 2001. "A framework for customer relationship management." California Management Review 43(4):89-105.   DOI   ScienceOn
26 Chang, J., Yen, D. C., Young, D., and Ku, C. Y. 2002. "Critical issues in CRM adoption and implementation." International Journal of Services Technology and Management 3(3):311-324.   DOI
27 Liu, D-R., and Shih, Y-Y. 2005. "Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences." The Journal of Systems and Software 77(2):181-191.   DOI   ScienceOn
28 Kim, Gye-Soo, and Xu, Da-Peng, 2013. "Excellence for Organization Quality Management Innovation Challenge-Comparison of Korea and China." Journal of Korean Society for Quality Management 41(4).