Fuzzy Modeling of Client Preference in Data-Rich Marketing Environments

16 Pages Posted: 26 Aug 2006

See all articles by Magne Setnes

Magne Setnes

Heineken Technical Services - Research and Development

U. Kaymak

Erasmus University Rotterdam (EUR) - Faculty of Economics - Department of Computer Science; Erasmus Research Institute of Management (ERIM)

Date Written: 13 2000, 11

Abstract

Advances in computational methods have led, in the world of financial services, to huge databases of client and market information. In the past decade, various computational intelligence (CI) techniques have been applied in mining this data for obtaining knowledge and in-depth information about the clients and the markets. This paper discusses the application of fuzzy clustering in target selection from large databases for direct marketing (DM) purposes. Actual data from the campaigns of a large financial services provider are used as a test case. The results obtained with the fuzzy clustering approach are compared with those resulting from the current practice of using statistical tools for target selection.

Keywords: direct marketing, client segmentation, fuzzy systems, fuzzy clustering

JEL Classification: M, M11, R4, M31, C8

Suggested Citation

Setnes, Magne and Kaymak, Uzay, Fuzzy Modeling of Client Preference in Data-Rich Marketing Environments (13 2000, 11). ERIM Report Series Reference No. ERS-2000-49-LIS. Available at SSRN: https://ssrn.com/abstract=370848

Magne Setnes

Heineken Technical Services - Research and Development ( email )

Smeetsweg 1
2382 PH, Zoeterwoude
Netherlands

Uzay Kaymak (Contact Author)

Erasmus University Rotterdam (EUR) - Faculty of Economics - Department of Computer Science ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM)

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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