Conference proceeding
Customer Churn Models: A Comparison of Probability and Data Mining Approaches
Looking Forward, Looking Back: Drawing on the Past to Shape the Future of Marketing Proceedings of the 2013 World Marketing Congress, pp.144-148
Developments in Marketing Science
AMS World Marketing Congress 2013 (Melbourne, Australia , 17/07/2013 - 20/07/2013)
2015
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Source: InCites
Abstract
As markets become increasingly saturated, astute companies acknowledge that their business strategies should focus on identifying those customers who are likely to churn (Hadden, Tiwari, Roy, & Ruta, 2007). Since net returns on investments for retention strategies are generally higher than for acquisitions, it is generally accepted that companies should concentrate their marketing resources to keep existing customers rather than to attract new ones (Colgate & Danaher, 2000). This calls for models capable of making accurate predictions about consumers’ behavior in a future time period. Such models should be able to specify which customers in a dataset have a higher probability to churn in a given future time period. Literature on churn modeling reveals that predictive models fall into one of two categories, namely probability modeling and data mining modeling. Although many studies from both of these streams have focused on developing models to predict and identify customer churn, to the best of our knowledge, none of them have compared the performance of these modeling approaches in terms of accuracy in identifying and predicting customer churn.
Details
- Title
- Customer Churn Models: A Comparison of Probability and Data Mining Approaches
- Creators
- Ali Tamaddoni Jahromi - Monash UniversityStanislav Stakhovych - Monash UniversityMichael Ewing - Monash University
- Contributors
- C Campbell (Editor)J J Ma (Editor)
- Publication Details
- Looking Forward, Looking Back: Drawing on the Past to Shape the Future of Marketing Proceedings of the 2013 World Marketing Congress, pp.144-148
- Conference
- AMS World Marketing Congress 2013 (Melbourne, Australia , 17/07/2013 - 20/07/2013)
- Series
- Developments in Marketing Science
- Publisher
- Springer Nature
- Number of pages
- 5
- Identifiers
- 991013134160302368
- Copyright
- © 2016 Academy of Marketing Science
- Academic Unit
- Faculty of Business, Law and Arts
- Language
- English
- Resource Type
- Conference proceeding