Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

A recommender system to avoid customer churn: A case study

12 references·7 citing·52 second hopsampled

FromToDepth

this work references cited by second hop· second hop is a sample of the most-cited connections

References

2003An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry411 cited
2005Customer segmentation and strategy development based on customer lifetime value: A case study338 cited
2005Predicting customer retention and profitability by using random forests and regression forests techniques308 cited
2005Methodology for customer relationship management307 cited
2004Predicting online-purchasing behaviour267 cited
2001Predicting customer potential value an application in the insurance industry234 cited
2004A purchase-based market segmentation methodology189 cited
2005Intelligent profitable customers segmentation system based on business intelligence tools157 cited
2003The implementation of customer profitability analysis: A case study114 cited
2002Predicting customer behavior in the market-space: a study of Rayport and Sviokla’s framework98 cited
2004A prediction model for the purchase probability of anonymous customers to support real time web marketing: a case study57 cited
2001Mixed-initiative synthesized learning approach for web-based CRM43 cited

Cited by

2024Using machine learning methods to predict future churners: an analysis of repeat hotel customers25 cited
2011Customer portfolio analysis using the SOM

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

25 cited

2018Maschinelles Lernen23 cited

2021A Stacking-Based Data Mining Solution to Customer Churn Prediction19 cited

2010Data Mining Applications in Customer Churn Management19 cited

2022Analysis of Telecom Churn using Machine Learning Techniques17 cited

2024Examining factors influencing the user’s loyalty on algorithmic news recommendation service14 cited