Internet Service Provider User Customer Lifetime Segmentation Analysis using RFM and K-Means Algorithm

Authors

  • Muhammad Febrian Rachmadhan Digital Business Study Program, Institut Desain dan Bisnis Bali, Indonesia
  • Mohamad Hafidhul Umam Faculty of Information Technology, Universitas Budi Luhur, Indonesia
  • Arief Wibowo Faculty of Information Technology, Universitas Budi Luhur, Indonesia
  • I Made Satrya Ramayu Digital Business Study Program, Institut Desain dan Bisnis Bali, Indonesia

DOI:

10.33395/sinkron.v9i1.13024

Keywords:

Customer Segmentation, Lifetime, Clustering, RFM, K-Means

Abstract

The characteristics of each customer can be segmented using RFM (Recency, Frequency, Monetary) which means customer's last transaction time, number of customer transactions, and amount of money spent. The Lifetime and K-Means methods are used to perform the process of clustering or grouping customers based on segmentation through RFM. The results will be divided into 4 clusters namely Gold, Silver, Platinum and Diamond. The results of clustering are visualized with graphs and cluster tables containing the results of segmentation and clusters or groups of From the results obtained from the previous stage, of the 104 customers in the Retail & Distribution Services (RDS) sector, 4 segments resulted in 43 customers with Platinum class, 39 customers with gold class, 14 customers with silver class, and 8 customers with platinum level. The most popular services services or product is high speed dedicated internet services, VPN IP package, and service network package as top 3 results. The largest amount of revenue services or product is transponder full time use services, support network and contact center application as top 3 results.

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Rachmadhan, M. F., Umam, M. H., Wibowo, A., & Ramayu, I. M. S. (2024). Internet Service Provider User Customer Lifetime Segmentation Analysis using RFM and K-Means Algorithm. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 9(1), 306-316. https://doi.org/10.33395/sinkron.v9i1.13024