Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services
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Cited by:
- M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
- Asamoah, Kwadwo, 2016. "On the credibility of insurance claim frequency: Generalized count models and parametric estimators," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 339-353.
- E Lima & C Mues & B Baesens, 2009. "Domain knowledge integration in data mining using decision tables: case studies in churn prediction," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(8), pages 1096-1106, August.
- Ali Dehghan & Theodore Trafalis, 2012. "Examining Churn and Loyalty Using Support Vector Machine," Business and Management Research, Business and Management Research, Sciedu Press, vol. 1(4), pages 153-161, December.
- Gattermann-Itschert, Theresa & Thonemann, Ulrich W., 2021. "How training on multiple time slices improves performance in churn prediction," European Journal of Operational Research, Elsevier, vol. 295(2), pages 664-674.
- Slãvescu Ecaterina Oana & Panait Iulian, 2012.
"Improving Customer Churn Models as one of Customer Relationship Management Business Solutions for the Telecommunication Industry,"
Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 1156-1160, May.
- Slavescu, Ecaterina & Panait, Iulian, 2012. "Improving customer churn models as one of customer relationship management business solutions for the telecommunication industry," MPRA Paper 44250, University Library of Munich, Germany.
- J. Burez & D. Van Den Poel, 2008. "Handling class imbalance in customer churn prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/517, Ghent University, Faculty of Economics and Business Administration.
- Vera Miguéis & Dirk Poel & Ana Camanho & João Falcão e Cunha, 2012.
"Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences,"
Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 337-353, December.
- V. L. Miguéis & D. Van Den Poel & A.S. Camanho & Joao Falcao E Cunha, 2012. "Predicting Partial Customer Churn Using Markov for Discrimination for Modeling First Purchase Sequences," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/806, Ghent University, Faculty of Economics and Business Administration.
- K. Coussement & D. Van Den Poel, 2008.
"Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers,"
Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium
08/527, Ghent University, Faculty of Economics and Business Administration.
- K. Coussement & D. van den Poel, 2009. "Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers," Post-Print halshs-00581595, HAL.
- J. Burez & D. Van Den Poel, 2005. "CRM at a Pay-TV Company: Using Analytical Models to Reduce Customer Attrition by Targeted Marketing for Subscription Services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/348, Ghent University, Faculty of Economics and Business Administration.
- Alvaro Arroyo & Alvaro Cartea & Fernando Moreno-Pino & Stefan Zohren, 2023. "Deep Attentive Survival Analysis in Limit Order Books: Estimating Fill Probabilities with Convolutional-Transformers," Papers 2306.05479, arXiv.org.
- B. Larivière & D. Van Den Poel, 2005. "Investigating the post-complaint period by means of survival analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/299, Ghent University, Faculty of Economics and Business Administration.
- B. Larivière & D. Van Den Poel, 2004. "Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/282, Ghent University, Faculty of Economics and Business Administration.
- A. Prinzie & D. Van Den Poel, 2005. "Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/292, Ghent University, Faculty of Economics and Business Administration.
- Prinzie, Anita & Van den Poel, Dirk, 2006. "Investigating purchasing-sequence patterns for financial services using Markov, MTD and MTDg models," European Journal of Operational Research, Elsevier, vol. 170(3), pages 710-734, May.
- Atakan Yalcin & Lerzan Aksoy & Timothy L. Keiningham & Bart Larivière & Sunil Mithas & Forrest V. Morgeson III, 2012. "The Satisfaction, Repurchase Intention and Shareholder Value Linkage: A Longitudinal Examination of Fixed and Firm Specific Effects," EcoMod2012 4543, EcoMod.
- Liu, Meijun & Hu, Xiao & Wang, Yuandi & Shi, Dongbo, 2018. "Survive or perish: Investigating the life cycle of academic journals from 1950 to 2013 using survival analysis methods," Journal of Informetrics, Elsevier, vol. 12(1), pages 344-364.
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More about this item
Keywords
Data mining; Customer relationship management; cross-sell analysis; multinomial probit; survival analysis; savings and investment features; retention behavior;
All these keywords.NEP fields
This paper has been announced in the following NEP Reports:- NEP-DCM-2004-06-02 (Discrete Choice Models)
- NEP-INO-2004-06-02 (Innovation)
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