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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation
16 references·0 citing·55 second hop
How can algorithms help in segmenting users and customers? 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References

  • 1989A Probabilistic Choice Model for Market Segmentation and Elasticity Structure1,348 cited
  • 2005Intelligent profitable customers segmentation system based on business intelligence tools157 cited
  • 2021Integrated Churn Prediction and Customer Segmentation Framework for Telco Business141 cited
  • 2017Customer segmentation in e-commerce: Applications to the cashback business model117 cited
  • 2023Interpretable machine learning-based approach for customer segmentation for new product development from online product reviews114 cited
  • 2008Approaches to Customer Segmentation104 cited
  • 2015Integrating multi-criteria decision making and clustering for business customer segmentation92 cited
  • 2011Estimating customer future value of different customer segments based on adapted RFM model in retail banking context90 cited
  • 2012Data accuracy's impact on segmentation performance: Benchmarking RFM analysis, logistic regression, and decision trees85 cited
  • 2013Customer Segmentation Using Clustering and Data Mining Techniques75 cited
  • 2011Segmenting customers in online stores based on factors that affect the customer’s intention to purchase74 cited
  • 2018Customer Segmentation in XYZ Bank Using K-Means and K-Medoids Clustering73 cited
  • 2016Customer lifetime value determination based on RFM model69 cited
  • 2008Improving Personalization Solutions through Optimal Segmentation of Customer Bases

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66 cited
  • 2021Customer segmentation by web content mining64 cited
  • 2015New approach to customer segmentation based on changes in customer value63 cited
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