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Predicting Customer Segment Changes to Enhance Customer Retention: A Case Study for Online Retail using Machine Learning
10 references·0 citing·52 second hop
Predicting Customer Segment Changes to Enhance Customer Retention: A Case Study for Online Retail using Machine Learning (2023)Predicting Customer Segment Changes to En…Improved Customer Lifetime Value Prediction With Sequence-To-Sequence Learning and Feature-Based Models (2021)Improved Customer Lifetime Va…Dynamics of customer segments: A predictor of customer lifetime value (2021)Dynamics of customer segments…Cognitive analytics management of the customer lifetime value: an artificial neural network approach (2021)Cognitive analytics managemen…Customer Segmentation Based on RFM Model Using K-Means, K-Medoids, and DBSCAN Methods (2020)Customer Segmentation Based o…Predicting customer value per product: From RFM to RFM/P (2019)Predicting customer value per…Market segmentation and travel choice prediction in Spa hotels through TripAdvisor’s online reviews (2019)Market segmentation and trave…RFM ranking – An effective approach to customer segmentation (2018)RFM ranking – An effective ap…Hybrid soft computing approach based on clustering, rule mining, and decision tree analysis for customer segmentation problem: Real case of customer-centric industries (2018)Hybrid soft computing approac…Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers (2017)Integration of Machine Learni…Customer lifetime value research in marketing: A review and future directions (2002)Customer lifetime value resea…Counting Your Customers: Who-Are They and What Will They Do Next? 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References

  • 2002Customer lifetime value research in marketing: A review and future directions583 cited
  • 2019Market segmentation and travel choice prediction in Spa hotels through TripAdvisor’s online reviews262 cited
  • 2018RFM ranking – An effective approach to customer segmentation214 cited
  • 2019Predicting customer value per product: From RFM to RFM/P92 cited
  • 2018Hybrid soft computing approach based on clustering, rule mining, and decision tree analysis for customer segmentation problem: Real case of customer-centric industries82 cited
  • 2020Customer Segmentation Based on RFM Model Using K-Means, K-Medoids, and DBSCAN Methods52 cited
  • 2021Improved Customer Lifetime Value Prediction With Sequence-To-Sequence Learning and Feature-Based Models46 cited
  • 2021Dynamics of customer segments: A predictor of customer lifetime value41 cited
  • 2021Cognitive analytics management of the customer lifetime value: an artificial neural network approach34 cited
  • 2017Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers33 cited

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