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Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining
1 references·16 citing·49 second hop
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this work references cited by second hop

References

  • 2005Customer Relationship Management: A Databased Approach288 cited

Cited by

  • 2019RFM model for customer purchase behavior using K-Means algorithm210 cited
  • 2014A decision-making framework for precision marketing106 cited
  • 2021RFM-based repurchase behavior for customer classification and segmentation96 cited
  • 2020An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K-Means Algorithm95 cited
  • 2023RFM model customer segmentation based on hierarchical approach using FCA87 cited
  • 2018Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty80 cited
  • 2020A hybrid big data analytical approach for analyzing customer patterns through an integrated supply chain network61 cited
  • 2017A novel model for product bundling and direct marketing in e-commerce based on market segmentation48 cited
  • 2021Improved Customer Lifetime Value Prediction With Sequence-To-Sequence Learning and Feature-Based Models46 cited
  • 2021Deep Learning for Customer Churn Prediction in E-Commerce Decision Support42 cited
  • 2019A Preliminary Study of Fintech Industry: A Two-Stage Clustering Analysis for Customer Segmentation in the B2B Setting37 cited
  • 2021Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes37 cited

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  • 2019RFM customer analysis for product-oriented services and service business development: an interventionist case study of two machinery manufacturers35 cited
  • 2021An Extended Regularized K-Means Clustering Approach for High-Dimensional Customer Segmentation With Correlated Variables35 cited
  • 2021User Value Identification Based on Improved RFM Model and K‐Means++ Algorithm for Complex Data Analysis33 cited
  • 2023Enhancing Retail Transactions: A Data-Driven Recommendation Using Modified RFM Analysis and Association Rules Mining31 cited