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    Measuring the costs and coverage of SME and entrepreneurship policy: A pioneering study

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    Publication type
    FT ranked journal article  
    Author
    Anders, L.
    Vikström, P.
    Fink, M.
    Meuleman, Miguel
    Glodek, P.
    Storey, D.
    Kroksgard, A.
    Publication Year
    2014
    Journal
    Entrepreneurship: Theory and Practice
    Publication Volume
    38
    Publication Issue
    4
    Publication Begin page
    941
    Publication End page
    957
    
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    Abstract
    Since 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.
    Keyword
    Customer Relationship Management
    Knowledge Domain/Industry
    Entrepreneurship
    DOI
    10.1111/etap.12037
    URI
    http://hdl.handle.net/20.500.12127/4850
    ae974a485f413a2113503eed53cd6c53
    10.1111/etap.12037
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