Abstract
Churn is the opposite of growth. Losing customers has serious impact on company’s overall performance. More specifically, means lost in sales and revenue, but also negative sentiment and potential negative impact to organization’s image for the competition. The increased importance of managing churn in subscription-based organizations, lead various efforts by subscription-based organizations to face the problem. Both, academic researchers and business practitioners, focusing on techniques around customer behavior forecasting. During the last years, various technologies have been used to forecast customer behavior in subscription-based organizations. To investigate further this area this paper aims to report on the research issues around customer churn and investigate previous customer churn prediction approaches in order to propose a new conceptual model for customer behavior forecasting.
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The publication of this paper has been partly supported by the University of Piraeus Research Centre.
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Katelaris, L., Themistocleous, M. (2017). Predicting Customer Churn: Customer Behavior Forecasting for Subscription-Based Organizations. In: Themistocleous, M., Morabito, V. (eds) Information Systems. EMCIS 2017. Lecture Notes in Business Information Processing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-65930-5_11
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DOI: https://doi.org/10.1007/978-3-319-65930-5_11
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