Customer Segmentation using RFM Model and K-Means Clustering

Authors

  • Rahul Shirole  Department of Computer Engineering, Vishwakarma Institute of Technology Pune, Maharashtra, India
  • Laxmiputra Salokhe  Department of Computer Engineering, Vishwakarma Institute of Technology Pune, Maharashtra, India
  • Saraswati Jadhav  Department of Computer Engineering, Vishwakarma Institute of Technology Pune, Maharashtra, India

DOI:

https://doi.org/10.32628/IJSRST2183118

Keywords:

RFM, Clustering, Silhouette Index.

Abstract

Today as the competition among marketing companies, retail stores, banks to attract newer customers and maintain the old ones is in its peak, every company is trying to have the customer segmentation approach in order to have upper hand in competition. So Our project is based on such customer clustering method where we have collected, analyzed, processed and visualized the customer’s data and build a data science model which will help in forming clusters or segments of customers using the k-means clustering algorithm and RFM model (Recency Frequency Monetary) for already existing customers. The input dataset we used is UK’s E-commerce dataset from UCI repository for Machine Learning which is based on customer’s purchasing behavioral. At the very simple the customer clusters would be like super customer, intermediate customers, customers on the verge of churning out based on RFM score .Along with this we also have created a web model where an e-commerce startup or e-commerce business analyst can analyze their own customers based on model we created .So using this it will be easy to target customers accordingly and achieve business strength by maintaining good relationship with the customers .

References

  1. Tushar Kansal; Suraj Bahuguna; Vishal Singh; Tanupriya ChoudhuryCustomer, “ Segmentation based on RFM model and Clustering Techniques With K-Means Algorithm”, IEEE 2018
  2. Muhammad Iqbal Dzulhaq ,Kartika Wulan Sari, Syaipul Ramdhan, Rahmat Tullah ,Sutarman,” Customer Segmentation Based on RFM Value Using K-Means Algorithm”, ICIC 2019
  3. Chaohua Liu,”Customer Segmentation and Evaluation Based On RFM, Cross- selling and Customer Loyalty”, IEEE 2011
  4. Shreya Tripathi1, Aditya Bhardwaj , Poovammal,” Approaches to Clustering in Customer Segmentation”, IJET 2018
  5. A.S.M. Shahadat Hossain,”Customer Segmentation using Centroid Based and Density Based Clustering Algorithms”, IEEE 2017

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Rahul Shirole, Laxmiputra Salokhe, Saraswati Jadhav "Customer Segmentation using RFM Model and K-Means Clustering" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 3, pp.591-597, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRST2183118