Analisa Segmentasi Customer Pada Perusahaan Bisnis Properties Menggunakan Model RFM (Kasus PT. Pollux Aditama Kencana)

Abstract

The current business development in the property industry is promising, leading to a highly competitive market. As a result, PT. Pollux Aditama Kencana, which operates in the property business, must have strategies in every market competition, especially in gaining customer loyalty. This study uses the Recency, Frequency, and Monetary (RFM) model combined with K-Means. The RFM model is used for customer data clustering based on the number of transaction activities, transaction amount, and transaction time. Meanwhile, K-Means can describe the level of customer loyalty. The data used in this study were taken from sales reports from November 28, 2014 to September 19, 2022, involving 1966 customers in property purchases. The results show that the proposed use of the RFM and K-Means models is superior compared to using only the RFM model. Cluster 1 has 936 customers, indicating customers with high loyalty to the company, while Cluster 2 has 250 customers, indicating customers with low loyalty, and Cluster 3 has 780 customers, indicating customers with medium loyalty. The RFM and K-Means models used successfully produced several loyalty attributes that affect customer evaluations, with 4% in the top customer category, 12% in the high-value customer category, 34% in the medium-value customer category, 31% in the low-value customer category, and 19% in the lost customer category.