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dc.contributor.advisorPretorius, P.D.
dc.contributor.authorVan der Westhuizen, Frederick Jacques
dc.date.accessioned2009-11-12T09:23:37Z
dc.date.available2009-11-12T09:23:37Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/10394/2521
dc.descriptionThesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.en
dc.description.abstractGiven the increase in popularity of Lifetime Value (LTV), the argument is that the topic will assume an increasingly central role in research and marketing. As such, the decision to assess the state of the field in Lifetime Value Modelling, and outline challenges unique to choice researchers in customer relationship management (CRM). As the research has argued, there are an excess of issues and analytical challenges that remain unresolved. The researcher hopes that this thesis inspires new answers and new approaches to resolve LTV. The scope of this project covers the building of a LTV model through multiple regression. This thesis is exclusively focused on modelling tenure. In this regard, there are a variety of benchmark statistical techniques arising from survival analysis, which could be applied, to tenure modelling. Tenure prediction will be looked at using survival analysis and compared with "crossbreed" data mining techniques that use multiple regression in concurrence with statistical techniques. It will be demonstrated how data mining tools complement the statistical models, and show that their mutual usage overcomes many of the shortcomings of each singular tool set, resulting in LTV models that are both accurate and comprehensible. Bank XYZ is used as an example and is based on a real scenario of one of the Banks of South Africa.en
dc.publisherNorth-West Universityen_US
dc.subjectLifetime valueen
dc.subjectCentral roleen
dc.subjectResearchen
dc.subjectMarketingen
dc.subjectModelling tenureen
dc.subjectData mining toolsen
dc.subjectStatistical techniquesen
dc.subjectMutual usageen
dc.subjectMultiple regressionen
dc.subjectStatistical modelsen
dc.titleLifetime value modellingen
dc.typeThesisen
dc.description.thesistypeMasters
dc.contributor.researchID10062432 - Pretorius, Philippus Daniël (Supervisor)


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