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Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty
10 references·3 citing·50 second hop
Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty (2015)Behavioral Modeling for Churn Prediction:…The effect of user features on churn in social networks (2011)The effect of user features o…Predicting customer churn through interpersonal influence (2011)Predicting customer churn thr…New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)New insights into churn predi…Social ties and their relevance to churn in mobile telecom networks (2008)Social ties and their relevan…Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Defection Detection: Measurin…Customer Metrics and Their Impact on Financial Performance (2006)Customer Metrics and Their Im…Bagging and Boosting Classification Trees to Predict Churn (2006)Bagging and Boosting Classifi…Turning telecommunications call details to churn prediction: a data mining approach (2002)Turning telecommunications ca…Customer lifetime value research in marketing: A review and future directions (2002)Customer lifetime value resea…Customer lifetime valuation to support marketing decision making (1997)Customer lifetime valuation t…Customer determinants of used auto loan churn: comparing predictive performance using machine learning techniques (2021)Customer determinants of used…Notice of Removal: ChOracle: A Unified Statistical Framework for Churn Prediction (2020)Notice of Removal: ChOracle: …Machine Learning Based Telecom-Customer Churn Prediction (2020)Machine Learning Based Teleco…Economic Action and Social Structure: The Problem of Embeddedness (1985)Social Ties and Word-of-Mouth Referral Behavior (1987)Birds of a Feather: Homophily in Social Networks (2001)A Hybrid Churn Prediction Model in Mobile Telecommunication Industry (2013)Time series for early churn detection: Using similarity based classification for dynamic networks (2018)Research on a Customer Churn Combination Prediction Model Based on Decision Tree and Neural Network (2020)Counting Your Customers: Who-Are They and What Will They Do Next? 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this work references cited by second hop

References

  • 2006Customer Metrics and Their Impact on Financial Performance916 cited
  • 2002Customer lifetime value research in marketing: A review and future directions583 cited
  • 2006Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models574 cited
  • 2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach460 cited
  • 2002Turning telecommunications call details to churn prediction: a data mining approach460 cited
  • 2006Bagging and Boosting Classification Trees to Predict Churn410 cited
  • 2008Social ties and their relevance to churn in mobile telecom networks105 cited
  • 2011Predicting customer churn through interpersonal influence72 cited
  • 2011The effect of user features on churn in social networks60 cited
  • 1997Customer lifetime valuation to support marketing decision making52 cited

Cited by

  • 2020Machine Learning Based Telecom-Customer Churn Prediction24 cited
  • 2020Notice of Removal: ChOracle: A Unified Statistical Framework for Churn Prediction19 cited
  • 2021Customer determinants of used auto loan churn: comparing predictive performance using machine learning techniques16 cited

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