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dc.contributor.authorAnders, L.
dc.contributor.authorVikström, P.
dc.contributor.authorFink, M.
dc.contributor.authorMeuleman, Miguel
dc.contributor.authorGlodek, P.
dc.contributor.authorStorey, D.
dc.contributor.authorKroksgard, A.
dc.date.accessioned2017-12-02T14:52:33Z
dc.date.available2017-12-02T14:52:33Z
dc.date.issued2014
dc.identifier.doi10.1111/etap.12037
dc.identifier.urihttp://hdl.handle.net/20.500.12127/4850
dc.description.abstractSince customer relationship management (CRM) plays an increasingly important role in a company’s marketing strategy, the database of the company can be considered as a valuable asset to compete with others. Consequently, companies constantly try to augment their database through data collection themselves, as well as through the acquisition of commercially available external data. Until now, little research has been done on the usefulness of these commercially available external databases for CRM. This study will present a methodology for such external data vendors based on random forests predictive modeling techniques to create commercial variables that solve the shortcomings of a classic transactional database. Eventually, we predicted spending pleasure variables, a composite measure of purchasing behavior and attitude, in 26 product categories for more than 3 million respondents. Enhancing a company’s transactional database with these variables can significantly improve the predictive performance of existing CRM models. This has been demonstrated in a case study with a magazine publisher for which prospects needed to be identified for new customer acquisition.
dc.language.isoen
dc.subjectCustomer Relationship Management
dc.titleMeasuring the costs and coverage of SME and entrepreneurship policy: A pioneering study
dc.identifier.journalEntrepreneurship: Theory and Practice
dc.source.volume38
dc.source.issue4
dc.source.beginpage941
dc.source.endpage957
vlerick.knowledgedomainEntrepreneurship
vlerick.typearticleFT ranked journal article  
vlerick.vlerickdepartmentEGS
dc.identifier.vperid168467
dc.identifier.vperid168469
dc.identifier.vperid168470
dc.identifier.vperid168472
dc.identifier.vperid58266
dc.identifier.vperid168471
dc.identifier.vperid168468
dc.identifier.vpubid5782


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