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dc.contributor.authorKridel, Don
dc.contributor.authorDolk, Dan
dc.date.accessioned2019-04-23T19:01:56Z
dc.date.available2019-04-23T19:01:56Z
dc.date.issued2004
dc.identifier.urihttps://hdl.handle.net/10945/62019
dc.descriptionPresented at Western Decision Sciences Institute (WDSI 2004) conferenceen_US
dc.description.abstractKridel and Dolk [1] describe a web-based service that uses advanced data mining and dynamic model building techniques to conduct intelligent profiling. This smart list approach is designed to assist small- to-medium businesses (SMBs) in leveraging their analytical marketing capabilities. We begin validation of this approach by comparing the performance of the smart list for one target company versus the service provided by one of the industry leaders in customer list generation. Initial results indicate that the smart list approach outperforms the traditional approach by a substantial margin for both response rate and ROI.en_US
dc.format.extent4 p.
dc.publisherWDSIen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleUsing Intelligent Profiling to Generate Smart Lists: An Empirical Testen_US
dc.typeConference Paperen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)en_US
dc.contributor.departmentInformation Sciences (IS)


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