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Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests

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References

2006Relationship quality as a predictor of B2B customer loyalty1,124 cited
2005RFM and CLV: Using Iso-Value Curves for Customer Base Analysis595 cited
2008Handling class imbalance in customer churn prediction552 cited
2018A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees529 cited
2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach460 cited
2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
2004Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting425 cited
2016The B2B Knowledge Gap380 cited
2017Retention Futility: Targeting High-Risk Customers Might be Ineffective292 cited
2006CRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services241 cited
2016A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry214 cited
2013The B2B Agenda: The current state of B2B marketing and a look ahead207 cited
2019Fostering B2B sales with customer big data analytics205 cited
2008Modeling churn using customer lifetime value

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187 cited

2008Quantitative models for direct marketing: A review from systems perspective182 cited

2016Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry161 cited

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2024Using machine learning methods to predict future churners: an analysis of repeat hotel customers25 cited
2022Customer Churn Prediction in B2B Non-Contractual Business Settings Using Invoice Data24 cited
2024Implementing machine learning techniques for customer retention and churn prediction in telecommunications21 cited