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Dynamic behavior based churn prediction in mobile telecom
9 references·16 citing·42 second hop
Dynamic behavior based churn prediction in mobile telecom (2020)Dynamic behavior based churn prediction i…Customer churn prediction in telecom using machine learning in big data platform (2019)Customer churn prediction in …Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)Retention Futility: Targeting…A comparison of machine learning techniques for customer churn prediction (2015)A comparison of machine learn…A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models (2012)A Novel Profit Maximizing Met…A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data (2012)A hierarchical multiple kerne…Computer assisted customer churn management: State-of-the-art and future trends (2005)Computer assisted customer ch…Applying data mining to telecom churn management (2005)Applying data mining to telec…Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2004)Customer base analysis: parti…Turning telecommunications call details to churn prediction: a data mining approach (2002)Turning telecommunications ca…Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)Customer Churn Prediction: A …Predictive analytics in customer behavior: Anticipating trends and preferences (2024)Predictive analytics in custo…ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry (2024)ChurnNet: Deep Learning Enhan…Machine learning based customer churn prediction in home appliance rental business (2023)Machine learning based custom…Hybrid model for profit-driven churn prediction based on cost minimization and return maximization (2023)Hybrid model for profit-drive…Development of a Customer Churn Model for Banking Industry Based on Hard and Soft Data Fusion (2023)Development of a Customer Chu…Deep Churn Prediction Method for Telecommunication Industry (2023)Deep Churn Prediction Method …Customer retention and churn prediction in the telecommunication industry: a case study on a Danish university (2023)Customer retention and churn …Predicting customer churn: A systematic literature review (2022)Predicting customer churn: A …Impact of Hyperparameters on Deep Learning Model for Customer Churn Prediction in Telecommunication Sector (2022)Impact of Hyperparameters on …Customer churn prediction for web browsers (2022)Customer churn prediction for…A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy (2022)A Swish RNN based customer ch…Predictive analytics for customer repurchase: Interdisciplinary integration of buy till you die modeling and machine learning (2021)Predictive analytics for cust…Effective ML Techniques to Predict Customer Churn (2021)Effective ML Techniques to Pr…An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation (2021)An analytical framework based…A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China (2021)A Prediction Model of Custome…Customer satisfaction, customer retention, and market share (1993)Understanding customer relationship management (CRM) (2003)The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services (2004)Customer churn prediction in telecommunications (2011)Customer churn prediction system: a machine learning approach (2021)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Handling class imbalance in customer churn prediction (2008)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)Social network analytics for churn prediction in telco: Model building, evaluation and network architecture (2017)Why you should stop predicting customer churn and start using uplift models (2019)Profit Driven Decision Trees for Churn Prediction (2020)Building Data Mining Applications for CRM (1999)Knowledge management and data mining for marketing (2001)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)Customer churn prediction in the telecommunication sector using a rough set approach (2016)In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions (2017)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Introduction to Data Mining (2007)Development and application of consumer credit scoring models using profit-based classification measures (2014)Improved churn prediction in telecommunication industry using data mining techniques (2014)Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)Zero defections: quality comes to services. (1990)The Commitment-Trust Theory of Relationship Marketing (1994)The Behavioral Consequences of Service Quality (1996)Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Customer churn prediction using improved balanced random forests (2008)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis (1999)A survey of results on mobile phone datasets analysis (2015)A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction (1998)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)The effect of social networks structure on innovation performance: A review and directions for research (2018)Digital Analytics: Modeling for Insights and New Methods (2020)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Customer churn prediction in telecommunication industry using data certainty (2018)Customer churn prediction in imbalanced datasets with resampling methods: A comparative study (2024)Customer churn prediction model based on hybrid neural networks (2024)Explaining customer churn prediction in telecom industry using tabular machine learning models (2024)Customer Churn Prediction in Telecom Sector Using Machine Learning Techniques (2022)A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners (2024)
this work references cited by second hop

References

  • 2005Applying data mining to telecom churn management514 cited
  • 2019Customer churn prediction in telecom using machine learning in big data platform486 cited
  • 2015A comparison of machine learning techniques for customer churn prediction470 cited
  • 2002Turning telecommunications call details to churn prediction: a data mining approach460 cited
  • 2004Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting425 cited
  • 2005Computer assisted customer churn management: State-of-the-art and future trends340 cited
  • 2017Retention Futility: Targeting High-Risk Customers Might be Ineffective292 cited
  • 2012A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models177 cited
  • 2012A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data146 cited

Cited by

  • 2023Deep Churn Prediction Method for Telecommunication Industry91 cited
  • 2022A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy71 cited
  • 2025Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning70 cited
  • 2024ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry65 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2021Effective ML Techniques to Predict Customer Churn61 cited
  • 2024Predictive analytics in customer behavior: Anticipating trends and preferences61 cited
  • 2023Machine learning based customer churn prediction in home appliance rental business59 cited
  • 2021Predictive analytics for customer repurchase: Interdisciplinary integration of buy till you die modeling and machine learning55 cited
  • 2022Impact of Hyperparameters on Deep Learning Model for Customer Churn Prediction in Telecommunication Sector48 cited
  • 2023Customer retention and churn prediction in the telecommunication industry: a case study on a Danish university42 cited
  • 2021An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation42 cited
  • 2021A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China41 cited
  • 2023Development of a Customer Churn Model for Banking Industry Based on Hard and Soft Data Fusion39 cited
  • 2022Predicting customer churn: A systematic literature review38 cited
  • 2023Hybrid model for profit-driven churn prediction based on cost minimization and return maximization35 cited
  • 2022Customer churn prediction for web browsers32 cited