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    Customer Relationship Management: from Conversion to Churn to Winback

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    Genre
    Thesis/Dissertation
    Date
    2013
    Author
    Li, Ke
    Advisor
    Di Benedetto, C. Anthony
    Eisenstein, Eric
    Committee member
    Bradlow, Eric T.
    Zhu, Ji
    Sarkar, S. K. (Sanat K.)
    Department
    Business Administration/Marketing
    Subject
    Marketing
    Crm
    Random Forests
    Winback
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/1735
    
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    DOI
    http://dx.doi.org/10.34944/dspace/1717
    Abstract
    With the grant of a big CRM dataset from a large media company, this dissertation examines four different categories of factors that could impact three stages of customer relationship management, namely customer acquisition, retention, and winback of lost customers. Specifically, with the aid of machine learning method of random forests and text mining technique, this study identify among the factors of customer heterogeneity (e.g. in usage of self-care service channels, duration of service, responsiveness to marketing actions), firm's marketing initiatives (e.g. the volume of the marketing communications, the depth of the promotion, the different communication channels they use, and the marketing penetration in different geographical areas), customer self-reported deactivation reasons, as well as the call centers notes in text form, which factors play bigger roles than others during each of the three stages of CRM. Furthermore, the authors also examine how these factors evolve throughout these three stages of CRM in terms of their effects on shaping customers' decision making of whether to convert to paid customer, to churn, or to reactivate their service with the company. The findings help managers better allocate their resources in the processes of acquiring, retaining and winning back customers.
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