Fuzzy Modeling of Client Preference in Data-rich Marketing Environments Magne Setnes and Uzay Kaymak Erasmus Research Institute of Management Report Series Research in Management Bibliographic Data and Classifications
نویسندگان
چکیده
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. 5001-6182 Business 5201-5982 Business Science Library of Congress Classification (LCC) HF 5415.126 Q 276-280 Direct Marketing Mathematical Statistics M Business Administration and Business Economics M 11 R 4 Production Management Transportation Systems Journal of Economic Literature (JEL) M 31 C 8 Marketing Data collection and data estimation methodology 85 A Business General 260 K 240 B Logistics Information Systems Management European Business Schools Library Group (EBSLG) 290 R 250 B Direct Marketing Fuzzy theory Gemeenschappelijke Onderwerpsontsluiting (GOO) 85.00 Bedrijfskunde, Organisatiekunde: algemeen 85.34 85.20 Logistiek management Bestuurlijke informatie, informatieverzorging Classification GOO 85.40 31.73 Marketing Mathematische Statistiek Bedrijfskunde / Bedrijfseconomie Bedrijfsprocessen, logistiek, management informatiesystemen
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