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Modeling churn using customer lifetime value

Citations

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Cited by:

  1. K. W. De Bock & D. Van Den Poel, 2012. "Reconciling Performance and Interpretability in Customer Churn Prediction using Ensemble Learning based on Generalized Additive Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/805, Ghent University, Faculty of Economics and Business Administration.
  2. Uner, M.Mithat & Guven, Faruk & Cavusgil, S.Tamer, 2020. "Churn and loyalty behavior of Turkish digital natives: Empirical insights and managerial implications," Telecommunications Policy, Elsevier, vol. 44(4).
  3. Oğuzhan Kivrak & Cüneyt Akar, 2020. "Effect of Social Media Interactions on CLV in Telecommunications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 447-468, March.
  4. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
  5. repec:dgr:rugsom:10008 is not listed on IDEAS
  6. Haupt, Johannes & Lessmann, Stefan, 2020. "Targeting Cutsomers Under Response-Dependent Costs," IRTG 1792 Discussion Papers 2020-005, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  7. Chen, Zhen-Yu & Fan, Zhi-Ping & Sun, Minghe, 2012. "A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data," European Journal of Operational Research, Elsevier, vol. 223(2), pages 461-472.
  8. Clemente-Císcar, M. & San Matías, S. & Giner-Bosch, V., 2014. "A methodology based on profitability criteria for defining the partial defection of customers in non-contractual settings," European Journal of Operational Research, Elsevier, vol. 239(1), pages 276-285.
  9. Sun, Yang, 2021. "Case based models of the relationship between consumer resistance to innovation and customer churn," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
  10. K. W. De Bock & D. Van Den Poel, 2011. "An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/717, Ghent University, Faculty of Economics and Business Administration.
  11. Johannes Haupt & Stefan Lessmann, 2020. "Targeting customers under response-dependent costs," Papers 2003.06271, arXiv.org, revised Aug 2021.
  12. Cherchye, Laurens & De Rock, Bram & Dierynck, Bart & Kerstens, Pieter Jan & Roodhooft, Filip, 2023. "A DEA-based approach to customer value analysis," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1319-1331.
  13. Li, Yixin & Hou, Bingzhang & Wu, Yue & Zhao, Donglai & Xie, Aoran & Zou, Peng, 2021. "Giant fight: Customer churn prediction in traditional broadcast industry," Journal of Business Research, Elsevier, vol. 131(C), pages 630-639.
  14. Laura Grassi & Nicolas Figini & Lorenzo Fedeli, 2022. "How does a data strategy enable customer value? The case of FinTechs and traditional banks under the open finance framework," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
  15. 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.
  16. Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
  17. Capponi, Giovanna & Corrocher, Nicoletta & Zirulia, Lorenzo, 2021. "Personalized pricing for customer retention: Theory and evidence from mobile communication," Telecommunications Policy, Elsevier, vol. 45(1).
  18. Tang, Leilei & Thomas, Lyn & Fletcher, Mary & Pan, Jiazhu & Marshall, Andrew, 2014. "Assessing the impact of derived behavior information on customer attrition in the financial service industry," European Journal of Operational Research, Elsevier, vol. 236(2), pages 624-633.
  19. 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.
  20. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
  21. Zihayat, Morteza & Ayanso, Anteneh & Davoudi, Heidar & Kargar, Mehdi & Mengesha, Nigussie, 2021. "Leveraging non-respondent data in customer satisfaction modeling," Journal of Business Research, Elsevier, vol. 135(C), pages 112-126.
  22. Höppner, Sebastiaan & Stripling, Eugen & Baesens, Bart & Broucke, Seppe vanden & Verdonck, Tim, 2020. "Profit driven decision trees for churn prediction," European Journal of Operational Research, Elsevier, vol. 284(3), pages 920-933.
  23. Latifah Almuqren & Fatma S. Alrayes & Alexandra I. Cristea, 2021. "An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach," Future Internet, MDPI, vol. 13(7), pages 1-19, July.
  24. Mirza Hassan Hosseini & Mahdi Rezaei, 2015. "Exploratory Study on Causes of Valuable Costumers Turnover in Irans Private Banking Industry (Case Study: Physician Specialists Society)," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 5(5), pages 251-260, May.
  25. de Wit, Jaap G. & Zuidberg, Joost, 2016. "Route churn: an analysis of low-cost carrier route continuity in Europe," Journal of Transport Geography, Elsevier, vol. 50(C), pages 57-67.
  26. Aurélie Lemmens & Sunil Gupta, 2020. "Managing Churn to Maximize Profits," Marketing Science, INFORMS, vol. 39(5), pages 956-973, September.
  27. Mahajan, Pravar Dilip & Maurya, Abhinav & Megahed, Aly & Elwany, Alaa & Strong, Ray & Blomberg, Jeanette, 2020. "Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1095-1113.
  28. Lessmann, Stefan & Coussement, Kristof & De Bock, Koen W. & Haupt, Johannes, 2018. "Targeting customers for profit: An ensemble learning framework to support marketing decision making," IRTG 1792 Discussion Papers 2018-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  29. Bijmolt, T.H.A. & Bl, 2010. "Should they stay or should they go? Reactivation and termination of low-tier customers," Research Report 10008, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  30. Valentini, Tony & Roederer, Claire & Castéran, Herbert, 2024. "From redesign to revenue: Measuring the effects of servicescape remodeling on customer lifetime value," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
  31. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W., 2018. "A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees," European Journal of Operational Research, Elsevier, vol. 269(2), pages 760-772.
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