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Towards Accurate Predictions of Customer Purchasing Patterns
10 references·0 citing·51 second hop
Towards Accurate Predictions of Customer Purchasing Patterns (2017)Towards Accurate Predictions of Customer …A decision-making framework for precision marketing (2014)A decision-making framework f…Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining (2012)Data mining for the online re…An extended support vector machine forecasting framework for customer churn in e-commerce (2010)An extended support vector ma…The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)The comparisons of data minin…Bank Customer Churn Prediction Based on Support Vector Machine: Taking a Commercial Bank's VIP Customer Churn as the Example (2008)Bank Customer Churn Predictio…Application of data mining techniques in customer relationship management: A literature review and classification (2008)Application of data mining te…Customer segmentation and strategy development based on customer lifetime value: A case study (2005)Customer segmentation and str…An integrated data mining and behavioral scoring model for analyzing bank customers (2004)An integrated data mining and…Predicting customer potential value an application in the insurance industry (2001)Predicting customer potential…Accelerating Customer Relationships: Using Crm and Relationship Technologies (2000)Accelerating Customer Relatio…Customer Relationship Management: A Databased Approach (2005)RFM model for customer purchase behavior using K-Means algorithm (2019)RFM-based repurchase behavior for customer classification and segmentation (2021)Why Satisfied Customers Defect (1996)Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry (2000)Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market (2004)Data Mining Applications in Customer Churn Management (2010)Churn Prediction in Customer Relationship Management via GMDH-Based Multiple Classifiers Ensemble (2016)Churn Prediction for Savings Bank Customers: A Machine Learning Approach (2020)Classifying the segmentation of customer value via RFM model and RS theory (2008)Application of decision-making techniques in supplier selection: A systematic review of literature (2012)Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems (2014)Can data-driven precision marketing promote user ad clicks? 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this work references cited by second hop

References

  • 2008Application of data mining techniques in customer relationship management: A literature review and classification1,267 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2000Accelerating Customer Relationships: Using Crm and Relationship Technologies434 cited
  • 2005Customer segmentation and strategy development based on customer lifetime value: A case study338 cited
  • 2012Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining252 cited
  • 2001Predicting customer potential value an application in the insurance industry234 cited
  • 2004An integrated data mining and behavioral scoring model for analyzing bank customers234 cited
  • 2014A decision-making framework for precision marketing106 cited
  • 2010An extended support vector machine forecasting framework for customer churn in e-commerce98 cited
  • 2008Bank Customer Churn Prediction Based on Support Vector Machine: Taking a Commercial Bank's VIP Customer Churn as the Example31 cited

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