Improving Customer Retention In Financial Services Using Kinship Network Information
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- Childers, Terry L & Rao, Akshay R, 1992. "The Influence of Familial and Peer-Based Reference Groups on Consumer Decisions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(2), pages 198-211, September.
- D. F. Benoit & D. Van Den Poel, 2009. "Benefits of Quantile Regression for the Analysis of Customer Lifetime Value in a Contractual Setting: An Application in Financial Services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/551, Ghent University, Faculty of Economics and Business Administration.
- Coussement, Kristof & Benoit, Dries Frederik & Van den Poel, Dirk, 2009.
"Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models,"
Working Papers
2009/18, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
- K. Coussement & D.F. Benoît & D. van den Poel, 2010. "Improved marketing decision making in a customer churn prediction context using generalized additive models," Post-Print halshs-00581701, HAL.
- K. Coussement & D. F. Benoit & D. Van Den Poel, 2009. "Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/603, Ghent University, Faculty of Economics and Business Administration.
- Charles F. Manski, 2000.
"Economic Analysis of Social Interactions,"
Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 115-136, Summer.
- Charles F. Manski, 2000. "Economic Analysis of Social Interactions," NBER Working Papers 7580, National Bureau of Economic Research, Inc.
- 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.
- 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.
- Peppard, Joe, 2000. "Customer Relationship Management (CRM) in financial services," European Management Journal, Elsevier, vol. 18(3), pages 312-327, June.
- Puneet Manchanda & Ying Xie & Nara Youn, 2008. "The Role of Targeted Communication and Contagion in Product Adoption," Marketing Science, INFORMS, vol. 27(6), pages 961-976, 11-12.
- Van den Poel, Dirk & Lariviere, Bart, 2004.
"Customer attrition analysis for financial services using proportional hazard models,"
European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
- D. Van Den Poel & B. Larivière, 2003. "Customer Attrition Analysis For Financial Services Using Proportional Hazard Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/164, Ghent University, Faculty of Economics and Business Administration.
- Lemmens, A. & Croux, C., 2006. "Bagging and boosting classification trees to predict churn," Other publications TiSEM d5cb664d-5859-44db-a621-e, Tilburg University, School of Economics and Management.
- Nair, Harikesh S. & Manchanda, Puneet & Bhatia, Tulikaa, 2006. "Asymmetric Peer Effects in Physician Prescription Behavior: The Role of Opinion Leaders," Research Papers 1970, Stanford University, Graduate School of Business.
- Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
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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.
- Senol Emir & Hasan Dincer & Umit Hacioglu & Serhat Yuksel, 2016. "Random Regression Forest Model using Technical Analysis Variables: An application on Turkish Banking Sector in Borsa Istanbul (BIST)," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 5(3), pages 85-102, April.
- Dogah, Kingsley E. & Premaratne, Gamini, 2018. "Sectoral exposure of financial markets to oil risk factors in BRICS countries," Energy Economics, Elsevier, vol. 76(C), pages 228-256.
- Louis Geiler & Séverine Affeldt & Mohamed Nadif, 2022. "A survey on machine learning methods for churn prediction," Post-Print hal-03824873, HAL.
- Ballings, Michel & Van den Poel, Dirk, 2015. "CRM in social media: Predicting increases in Facebook usage frequency," European Journal of Operational Research, Elsevier, vol. 244(1), pages 248-260.
- Gaurav Gupta & Himanshu Aggarwal, 2016. "Analysing customer responses to migrate strategies in making retailing and CRM effective," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 12(1), pages 92-127.
- Pal, Abhipsa & Herath, Tejaswini & De', Rahul & Raghav Rao, H., 2021. "Why do people use mobile payment technologies and why would they continue? An examination and implications from India," Research Policy, Elsevier, vol. 50(6).
- Arno de Caigny & Kristof Coussement & Koen W. de Bock & Stefan Lessmann, 2019. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," Post-Print hal-02275958, HAL.
- Arthur J. Lin & Hai-Yen Chang & Sun-Weng Huang & Gwo-Hshiung Tzeng, 2021. "Criteria affecting Taiwan wealth management banks in serving high-net-worth individuals during COVID-19: a DEMATEL approach," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(4), pages 274-294, December.
- De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan, 2020. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1563-1578.
- Jiaming Liu & Chong Wu & Yongli Li, 2019. "Improving Financial Distress Prediction Using Financial Network-Based Information and GA-Based Gradient Boosting Method," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 851-872, February.
- Yanhao Wei & Pinar Yildirim & Christophe Van den Bulte & Chrysanthos Dellarocas, 2016. "Credit Scoring with Social Network Data," Marketing Science, INFORMS, vol. 35(2), pages 234-258, March.
- Mitrović, Sandra & Baesens, Bart & Lemahieu, Wilfried & De Weerdt, Jochen, 2018. "On the operational efficiency of different feature types for telco Churn prediction," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1141-1155.
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More about this item
Keywords
network based marketing; CRM; predictive analystics; social network analysis (SNA); kinship network; financial services; random forests;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-FOR-2012-10-20 (Forecasting)
- NEP-NET-2012-10-20 (Network Economics)
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