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Integrating the voice of customers through call center emails into a decision support system for churn prediction

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  • K. Coussement

    (UMR CNRS 8179 - Université de Lille, Sciences et Technologies - CNRS - Centre National de la Recherche Scientifique)

  • D. van den Poel

Abstract

We studied the problem of optimizing the performance of a DSS for churn prediction. In particular, we investigated the beneficial effect of adding the voice of customers through call center emails – i.e. textual information - to a churn prediction system that only uses traditional marketing information. We found that adding unstructured, textual information into a conventional churn prediction model resulted in a significant increase in predictive performance. From a managerial point of view, this integrated framework helps marketing-decision makers to identify customers most prone to switch. Consequently, their customer retention campaigns can be targeted effectively because the prediction method is better at detecting those customers who are likely to leave.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • K. Coussement & D. van den Poel, 2008. "Integrating the voice of customers through call center emails into a decision support system for churn prediction," Post-Print hal-00788086, HAL.
    • Handle: RePEc:hal:journl:hal-00788086
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