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Importance-Induced Customer Segmentation Using Explainable Machine Learning
16 references·0 citing·50 second hop
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References

  • 1956Product Differentiation and Market Segmentation as Alternative Marketing Strategies1,953 cited
  • 2022Interviews in the social sciences939 cited
  • 2003An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry420 cited
  • 2020What Makes an Online Review More Helpful: An Interpretation Framework Using XGBoost and SHAP Values321 cited
  • 2007Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression320 cited
  • 2021Artificial Intelligence–Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study299 cited
  • 2007Customer segmentation revisited: The case of the airline industry197 cited
  • 2018Customer Segmentation using K-means Clustering186 cited
  • 1998A practical yet meaningful approach to customer segmentation167 cited
  • 2023Interpretable machine learning-based approach for customer segmentation for new product development from online product reviews114 cited
  • 2008Approaches to Customer Segmentation104 cited
  • 2011A Survey of the Challenges and Pifalls of Cluster Analysis Application in Market Segmentation68 cited
  • 2015A Data-Driven Network Analysis Approach to Predicting Customer Choice Sets for Choice Modeling in Engineering Design41 cited
  • 2018

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A Case Study on Customer Segmentation by using Machine Learning Methods
33 cited
  • 2022Customer Segmentation via Data Mining Techniques: State-of-the-Art Review31 cited
  • 2023Extracting product design guidance from online reviews: An explainable neural network-based approach18 cited
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