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Customer Churn Prediction using Machine Learning Models
12 references·2 citing·47 second hop
Customer Churn Prediction using Machine Learning Models (2024)Customer Churn Prediction using Machine L…Customer churning analysis using machine learning algorithms (2023)Customer churning analysis us…Customer churn prediction using composite deep learning technique (2023)Customer churn prediction usi…Machine Learning to Develop Credit Card Customer Churn Prediction (2022)Machine Learning to Develop C…Customer Churn Prediction in Influencer Commerce: An Application of Decision Trees (2022)Customer Churn Prediction in …A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy (2022)A Swish RNN based customer ch…A Data-Driven Approach to Improve Customer Churn Prediction Based on Telecom Customer Segmentation (2022)A Data-Driven Approach to Imp…Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms (2021)Dynamic customer churn predic…Customer churn prediction system: a machine learning approach (2021)Customer churn prediction sys…Churn Prediction in Telecommunication using Logistic Regression and Logit Boost (2020)Churn Prediction in Telecommu…Big data technologies: An empirical investigation on their adoption, benefits and risks for companies (2017)Big data technologies: An emp…A comparison of machine learning techniques for customer churn prediction (2015)A comparison of machine learn…Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Churn prediction in subscript…RetenNet: A Deployable Machine Learning Pipeline with Explainable AI and Prescriptive Optimization for Customer Churn Management (2025)RetenNet: A Deployable Machin…MNeuralTab: Integrating meta-modeling and neural networks for customer churn prediction in e-commerce (2025)MNeuralTab: Integrating meta-…A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing (1998)Switching barriers and repurchase intentions in services (2000)Customer churn prediction using improved balanced random forests (2008)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Customer churn prediction in telecommunications (2011)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Turning telecommunications call details to churn prediction: a data mining approach (2002)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions (2017)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Big Data : The Management Revolution (2013)Beyond the hype: Big data concepts, methods, and analytics (2014)People analytics—A scoping review of conceptual boundaries and value propositions (2018)Big Data Analytics in Building the Competitive Intelligence of Organizations (2020)Building dynamic capabilities by leveraging big data analytics: The role of organizational inertia (2020)A novel evolutionary data mining algorithm with applications to churn prediction (2003)Customer churn prediction in the telecommunication sector using a rough set approach (2016)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM (2022)Customer Churn Prediction in Telecom Sector Using Machine Learning Techniques (2022)Deep Churn Prediction Method for Telecommunication Industry (2023)Handling class imbalance in customer churn prediction (2008)Customer churn prediction in telecom using machine learning in big data platform (2019)A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners (2024)The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services (2004)The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication market (2005)Latent Variable Models and Factor Analysis (2011)Intelligent Decision Forest Models for Customer Churn Prediction (2022)Customer Churn Prediction in the Banking Sector Using Machine Learning-Based Classification Models (2023)Hyper-Personalization for Enhancing Customer Loyalty and Satisfaction in Customer Relationship Management (CRM) Systems (2023)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries (2023)Predictive Churn Modeling for Sustainable Business in the Telecommunication Industry: Optimized Weighted Ensemble Machine Learning (2023)Ensemble-based deep learning techniques for customer churn prediction model (2024)Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market (2004)Computer assisted customer churn management: State-of-the-art and future trends (2005)Customer churn prediction by hybrid neural networks (2009)Customer churn prediction model based on hybrid neural networks (2024)Opportunities and Challenges of Marketing 5.0 (2024)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)Customer Churn Prediction in Telecommunication Industry Using Deep Learning (2022)ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry (2024)A Comprehensive Evaluation of Machine Learning and Deep Learning Models for Churn Prediction (2025)AI-Based Customer Churn Prediction Model for Business Markets in the USA: Exploring the Use of AI and Machine Learning Technologies in Preventing Customer Churn (2024)Improving Churn Detection in the Banking Sector: A Machine Learning Approach with Probability Calibration Techniques (2024)A data-driven approach with explainable artificial intelligence for customer churn prediction in the telecommunications industry (2025)
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References

  • 2015A comparison of machine learning techniques for customer churn prediction470 cited
  • 2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
  • 2017Big data technologies: An empirical investigation on their adoption, benefits and risks for companies385 cited
  • 2021Customer churn prediction system: a machine learning approach328 cited
  • 2020Churn Prediction in Telecommunication using Logistic Regression and Logit Boost160 cited
  • 2023Customer churning analysis using machine learning algorithms95 cited
  • 2023Customer churn prediction using composite deep learning technique82 cited
  • 2022Machine Learning to Develop Credit Card Customer Churn Prediction79 cited
  • 2022A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy71 cited
  • 2022A Data-Driven Approach to Improve Customer Churn Prediction Based on Telecom Customer Segmentation65 cited
  • 2021Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms62 cited
  • 2022Customer Churn Prediction in Influencer Commerce: An Application of Decision Trees51 cited

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  • 2025MNeuralTab: Integrating meta-modeling and neural networks for customer churn prediction in e-commerce9 cited

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  • 2025RetenNet: A Deployable Machine Learning Pipeline with Explainable AI and Prescriptive Optimization for Customer Churn Management9 cited