Abstract
In this paper, we propose the customer map – the information visualization method for customer targeting. To develop the customer map, we classify customer data into customer needs, customer characteristics, and customer value. We suggest an analysis framework to derive key dimensions of the customer map by data mining techniques and a network mapping method to detect meaningful combinations of key dimensions. The customer map is built visually in terms of these key dimensions. The proposed visual targeting model helps a decision maker to build customer-oriented strategies and offers them the ability to monitor and perceive the real time state of customer value distribution based on their information without preconception. We apply the visual targeting model to a credit card company, and acquire managerial implications from this study.
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© 2005 Springer-Verlag Berlin Heidelberg
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Woo, J.Y., Bae, S.M., Pyon, C.U., Choi, M.S., Park, S.C. (2005). Visual Mining for Customer Targeting. In: Zhang, Y., Tanaka, K., Yu, J.X., Wang, S., Li, M. (eds) Web Technologies Research and Development - APWeb 2005. APWeb 2005. Lecture Notes in Computer Science, vol 3399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31849-1_94
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DOI: https://doi.org/10.1007/978-3-540-31849-1_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25207-8
Online ISBN: 978-3-540-31849-1
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