Customer Clustering Based on RFM Features Using K-Means Algorithm
Author:
Affiliation:
1. University of Brawijaya,Intelligent System Laboratory, Faculty of computer science,Malang,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9865234/9865242/09865572.pdf?arnumber=9865572
Reference14 articles.
1. Customer Segmentation Using Two-Step Mining Method Based on RFM Model
2. Customer clustering using RFM analysis
3. RFM-based repurchase behavior for customer classification and segmentation
4. Discovering valuable frequent patterns based on RFM analysis without customer identification information
5. What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Customer Relationships Management (CRM) Application for Customer Segmentation via RFM Analysis and K-Means Clustering;Advances in Science, Technology & Innovation;2024
2. Research on the Classification of E-Commerce Users Based on RFM Model and K-Means Algorithm;2023 IEEE International Conference on Electrical, Automation and Computer Engineering (ICEACE);2023-12-29
3. A Study of Customer Segmentation Based on RFM Analysis and K-Means;International Conference on Innovative Computing and Communications;2023-10-26
4. Analysis of Customer Clustering for Make-To-Order Manufacturing Company;2023 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C);2023-08-24
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