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LSI based profitability prediction of new customers

: Thorleuchter, D.; Poel, D. van den; Prinzie, A.

Fulltext urn:nbn:de:0011-n-1635215 (224 KByte PDF)
MD5 Fingerprint: a3ddde96450a721bb90c659d853b33d4
Created on: 2.6.2011

Yada, K. ; Society for Industrial and Applied Mathematics -SIAM-, Philadelphia/Pa.:
Data mining for marketing : SIAM International Workshop on Data Mining for Marketing held in conjunction with the 2011 SIAM International Conference on Data Mining, Saturday, April 30, 2011
International Workshop on Data Mining for Marketing (DMM) <2011, Mesa/Ariz.>
International Conference on Data Mining (SDM) <11, 2011, Mesa/Ariz.>
Conference Paper, Electronic Publication
Fraunhofer INT ()
text mining; web mining; information extraction; classification

This study investigates the impact of website information from existing business customers of a company on the prediction of the profitability of new business customers. Estimating the profitability of new customers is a well-known problem in acquisition management. Thus, the results of this study can be used to advance the acquisition process of a company.
A methodology is provided and the acquisition process of a mail order company is supported by use of this methodology. This case study shows that information of existing customers' websites can be used as successful classifier by modeling the profitability prediction. Thus, new profitable business customers can be acquired by the company.