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Vol: 57(71) No: 1 / March 2012 Credit Users Segmentation for Improved Customer Relationship Management in Banking Z. Bošnjak University of Novi Sad, Faculty of Economics, Subotica, Serbia, e-mail: bzita@ef.uns.ac.rs O. Grljević University of Novi Sad, Faculty of Economics, Subotica, Serbia, e-mail: oliverag@ef.uns.ac.rs Keywords: credit users segmentation, customer relationship management, banking, customer-centric strategy Abstract Nowadays, extreme competition on the one hand, and customers’ involvement in shaping the supply, on the other hand, has conditioned the success of a modern companies by knowledge of the characteristics, desires, preferences and habits of their customer base. Contemporary trends imposed to the companies a need to develop customer-centric strategy. This strategy makes customers the focus of a business, directing all efforts of the company to the maximum satisfaction of customers\' needs and desires. One of the techniques of data mining, widespread in customer relationship management, is customer segmentation. The goal of customer segmentation is to group customers by common characteristics in the way that created segments are profitable and growing which will enable companies to target each segment with specific offerings. Results obtained by this analysis enable companies to get closer to customers and truly implement in practice customer-centric strategy. Application of customer segmentation technique is illustrated on the example of a credit card users, pointing out the ways in which intelligent methods and techniques allow the identification of existing good bank customers (customers who do not have a problem with payment) and possibilities to use these results to predict future clients with the same characteristics. References [1] A. Beerson, S. Smith, and K. Thearling, Customer Acquisition and Data Mining, [Online] Available http://www.thearling.com/text/chapter10/chapter10.htm, December 21, 2010. [2] B. R. Grover, How To Segment Customers, Modern Distribution Management - the Newsletter for the Wholesale Distribution Channel, 2004, [Online] available at http://www.mdm.com/issues/cgi-bin/udt/im.display.printable?client_id=mdm&story_id=2155 [3] C. Rygielski, J.-C. Wang, and D. C. Yen, “Data Mining Techniques for Customer Relationship Management”, Technology in Society, vol. 24, no. 32, pp. 483–502, 2002. [4] C. J. Bucholtz, How Customer Segmentation Can Unravel CRM, CRM Buyer, 2010. [5] Customer DNA, Data Mining & Market Research in Segmentation Management, September 2010, [Online] Available http://www.customers-dna.com/index.php?page=shop.product_details&flypage=tpflypage.tpl&product_id=51&category_id=14&option=com_virtuemart&Itemid=53 [6] S. Dimitriadis, A. Kouremenos, and N. Kyrezis, “Trust-based segmentation. Preliminary evidence from technology-enabled bank channels”, International Journal of Bank Marketing, vol. 29, no. 1, pp. 5–31, 2011. [7] T. Foscht, C. Maloles II, B. Swoboda, and S. L. Chia, “Debit and credit card usage and satisfaction. Who uses which and why – evidence from Austria”, International Journal of Bank Marketing, vol. 28, no. 2, pp. 150–165, 2010. [8] H. Hwang, T. Jung, and E. Suh, “An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry”, Expert Systems with Applications, vol. 26, pp. 181–188, 2004. [9] J. Srivastava, Data Mining for Customer Relationship Management, [Online] Available http://www.dtc.umn.edu/ddmc/resources/crm.pdf, January15, 2011. [10] K. Tsiptsis and A. Chorianopoulos, Data Mining Techniques in CRM Inside Customer Segmentation, John Wiley & Sons, Ltd, 2009. [11] K. Thearling, Data Mining and Customer Relationships, [Online] Available http://www.thearling.com/text/whexcerpt/whexcerpt.htm, January 15, 2011. [12] P. Cruz, L. Barretto Filgueiras Neto, P. Muñoz-Gallego, and T. Laukkanen, |Mobile banking rollout in emerging markets: evidence from Brazil”, International Journal of Bank Marketing, vol. 28, no. 5, pp. 342–371, 2010. [13] Rosella Predictive Knowledge & Data Mining, Customer segmentation, [Online] Available http://www.roselladb.com/customer-segmentation.htm, November 28, 2010. [14] Rosella Predictive Knowledge & Data Mining, Insurance Risk Analysis, [Online] Available http://www.roselladb.com/insurance-risk-analysis.htm, November 28, 2010. [15] W. Li, Y. Sun, X. Wu, and Q. Zhang, “Credit Card Customer Segmentation and Target Marketing Based on Data Mining”, Proceedings of International Conference on Computational Intelligence and Security, 2010, pp 73–76. [16] U. A. Zafari, I. Ishak, M. Sadiq Sohail, I. Tabsh, and H. Alias, “Malaysian consumers’ credit card usage behavior”, Asia Pacific Journal of Marketing and Logistics, vol. 22, no. 4, pp. 528–544, 2010. |