An analysis of structural changes of customer segments by a hybrid method of clustering and association rule

Document Type : Research Paper

Authors

1 PhD Student of Industrial Engineering, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran

3 Associate Professor, Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Customer segmentation is one of the main and key issues in customer relationship management studies. One of the main challenges of customer segmentation is segments’ instability and changes over time. Segments’ changes can be categorized into two main categories including structural and content changes. The focus of this paper is on the structural change which is very important. To analyze the structural changes, a hybrid method of clustering and association rule mining techniques is presented and implemented on the data of a main service provider in telecommunication industry in Iran. Based on the results, the structural changes are categorized into cyclic changes and changes with trend which are discussed. The results show that a growing trend has been formed implying creation of a new segment in this corporation. The results provide the marketing managers with useful knowledge to make more effective marketing decisions.   

Keywords

Main Subjects

References

Achrol, R. S. & Etzel, M. J. (2003). The structure of reseller goals and performance in marketing channels, Journal of the Academy of Marketing Science, 31(2): 146- 163.
Ahmadi, P., azar, A. & Samsami, F. (2011). Market segmentation using neural networks (Case study: Pharmaceutical market in iran), Journal of Business Management, 2(6):1- 20. (In Persian)
Akhondzadeh-Noughabi, E., Albadvi, A. & Aghdasi, M. (2014). Mining customer dynamics in designing customer segmentation using data mining techniques, Information Technology Management, 6(1): 1- 30. (In Persian)
Blocker, C. P. & Flint, D. J. (2007). Customer segments as moving targets: integrating customer value dynamism into segment instability logic, Industrial Marketing Management, 36(6): 810– 822.
Bottcher, M., Spott, M., Nauck, D. & Kruse, R. (2009). Mining changing customer segments in dynamic markets, Expert Systems with Applications, 36(1): 155- 164.
Brangule-Vlagsma, K., Pieters, R. G. M. & Wedel, M. (2002). The dynamics of value segments: Modeling framework and empirical illustration, International Journal of Research in Marketing, 19: 267– 285.
Buckinxa, W., Moonsb, E. & Wetsb, G. (2004). Customer-adapted coupon targeting using feature selection, Expert Systems with Applications, 26(4): 509– 518.
Chen, M. C., Chiu, A. L., & Chang, H. H. (2005). Mining changes in customer behavior in retail marketing, Expert Systems with Applications, 28(4): 773-781.
Cheng, Ch. H. & Chen, Y. Sh. (2009). Classifying the segmentation of customer value via RFM model and RS theory, Expert systems with applications, 36(3): 4176– 4184.
Cheng, L. C., & Sun, L. M. (2012). Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: An empirical case study, Electronic Commerce Research and Applications, 11: 89–100.
Chong, Y. T. & Chen, C. H. (2010). Customer needs as moving targets of product development: A review, The International Journal of Advanced Manufacturing Technology, 48(1-4): 395- 406.
Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2): 224- 227.
Dibb, S. (1998). Market segmentation: strategies for success, Marketing Intelligence and Planning, 16(7): 394– 406.
Dickson, P. R. (1994). Marketing management, Dryden Press, Orlando, FL.
Durango-Cohen, E. J. (2013). Modeling contribution behavior in fundraising: Segmentation analysis for a public broadcasting station, European Journal of Operational Research, 227(3): 538- 551.
Esfidani, M. R., et al. (2014). Retail banking market segmentation based on the expected benefits of Bank Mellat customers, Journal of Business Management,6(2): 227-250. (In Persian)
Farley, J. U., Winer, R. S. & Lehmann, D. R. (1987). Stability of membership in market segments identified with a disaggregate consumption model, Journal of Business research, 15(4): 313- 328.
Ha, S. H. & Bae, S. M. (2006). Keeping track of customer life cycle to build customer relationship, In Advanced Data Mining and Applications, Berlin, Heidelberg: Springer Berlin Heidelberg, PP. 372-379.
Ha, S. H. (2007). Applying knowledge engineering techniques to customer analysis in the service industry, Advanced Engineering Informatics, 21(3): 293- 301.
Ha, S. H., Bae, S. M. & Park, S. C. (2002). Customer's time-variant purchase behavior and corresponding marketing strategies: an online retailer's case, Computers & Industrial Engineering, 43: 801- 820.
Haining, T., Juanjuan, Xu. & Bian, Zh. (2009). Research on index system of dynamic customer segmentation, International Conference on Information Management and Engineering, 441- 445, 3- 5, Kuala Lumpur, Malaysia.
Han, J. & Kamber, M. (2006). Data Mining: Concepts and Techniques, 2nd edition, Morgan Kaufmann Publisher, San Francisco.
Hoek, J., Gendall, P. & Esslemont, D. (1993). Market segmentation: A search for the Holy Grail, Asia-Australia Marketing Journal, 1(1): 41-46.
Homburg, Ch., Steiner, V. V. & Totzek, D. (2009). Managing dynamics in a customer portfolio, Journal of Marketing, 73(5): 70- 89.
Hossein zadeh, S., Karami, M., & Mehrbani, M. (2015). Segmentation of customers based on food related lifestyle scale at chain restaurants (Case study: Boof fast food chain restaurants in tehran, Journal of BusinessManagement, 1(7): 83- 99. (In Persian)
Hu, M. Y. & Rau, P. A. (1995). Stability of usage segments, membership shifts across segments and implications for marketing strategy-an empirical examination, Midatlantic Journal of Business, 31(2): 161-177.
Joshi, A. W. & Campbell, A. J. (2003). Effect of environmental dynamism on relational governance in manufacturer-supplier relationships: A contingency framework and an empirical test, Journal of the Academy of Marketing Science, 31(2): 176- 188.
Khajvand, M. & Tarokh, M. J. (2011). Estimating customer future value of different customer segments based on adapted RFM model in retail banking context, Procedia Computer Science, 3: 1327-1332.
Kim, J. K., Song, H. S., Kim, T. S., & Kim, H. K. (2005). Detecting the change of customer behavior based on decision tree analysis, Expert Systems, 22(4): 193-205.
Lemmens, A., Croux, C. h. & Stremersch, S. (2012). Dynamics in the international market segmentation of new product growth, International Journal of Research in Marketing, 29(1): 81-92.
Liu, B., Hsu, W., Han, H. S. & Xia, Y. (2000). Mining changes for real-life applications, In Data Warehousing and Knowledge Discovery, 337-346, 4- 6, London, UK.
Liu, D. R., Lai, C. H., & Lee, W. J. (2009). A hybrid of sequential rules and collaborative filtering for product recommendation, Information Sciences, 179(20): 3505- 3519.
Liu, D. R. & Shih, Y. Y. (2005). Integrating AHP and data mining for product recommendation based on customer lifetime value, Information and Management, 42(3): 387– 400.
Mitchell, V. W. & Wilson, D. F. (1998). Balancing theory and practice: A reappraisal of business-to-business segmentation, Industrial Marketing Management4, 27(5): 29- 445.
Mollahosseini, A. & Alimirzaei, G. R. (2011). Segmentation and identifying the characteristics of customers of irankhodro & saipa groups in kerman city, Journal of Business Management, 2(6): 135- 146. (In Persian)
Netzer, O., Lattin, J. M. & Srinivasan, V. (2008). A hidden Markov model of customer relationship dynamics, Marketing Science, 27: 185–204.
Newell, F. (1997). The new rules of marketing: How to use one-to-one relationship marketing to be the leader in your industry, McGraw-Hills Companies Inc, New York.
Ngai, E. W. T., Xiu, Li. & Chau, D. C. K. (2009). Application of data mining techniques in customer relationship management: A literature review and classification, Expert Systems with Applications, 36(2): 2592– 2602.
Reutterer, T., Mild, A., Natter, M., & Taudes, A. (2006). A dynamic segmentation approach for targeting and customizing direct marketing campaigns, Journal of Interactive Marketing, 20(3-4): 43-57.
Saunders, M. & Lewis, Ph. (2009). Research Methods for Business Students, Adrian ThornhillPrentice Hall, London.
Steenkamp, J. B. E. & Hofstede, F. (2002). International market segmentation: issues and perspectives, International Journal of Research in Marketing, 19(3): 185- 213.
Tan, P. N., Steinbach, M. & Kumar, V. (2006). Introduction to data mining, Pearson Education Inc, Boston, MA.
Tsiptsis, K. & Chorianopoulos, A. (2009). Data mining techniques in CRM: Inside customer segmentation, John Wiley & Sons, Chichester.
Wang, Z. & Lei, X. (2010). Study on customer retention under dynamic markets, In Networks Security Wireless Communications and Trusted Computing (NSWCTC), 2: 514-517, 24- 25, April, Wuhan, Hubei.
Wedel, M. & Kamakura, W. (2002). Introduction to the special issue on market segmentation, International Journal of Research in Marketing, 19(3): 181-183.

Files

Share

How to cite

Statistics