Setiawan, Dolis
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Customer Segmentation Based on RFM Analysis as the Basis of Marketing Strategy: A Case Study of Ultra Fiber Optic (UFO) Internet Customers of PT Ultra Mandiri Telekomunikasi in Jabodetabek Setiawan, Dolis; Heikal, Jerry
Journal Research of Social Science, Economics, and Management Vol. 5 No. 8 (2026): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i8.1353

Abstract

Abstract. The Internet Service Provider (ISP) industry in the Jabodetabek region has entered a critical red ocean phase, characterized by hyper-competition, aggressive price wars, and market saturation, with over 1,000 active providers. PT Ultra Mandiri Telekomunikasi (PT UMT), traditionally a B2B infrastructure company, faces significant challenges in its strategic diversification into the B2C retail market through its brand, Ultra Fiber Optic (UFO). To address high churn rates and inefficient mass marketing, this study aims to develop a precision segmentation strategy using a Mixed-Method Sequential Explanatory design. This approach integrates quantitative RFM (Recency, Frequency, Monetary) analysis with qualitative ethnographic research to formulate a targeted marketing strategy. Using a validated dataset of 629 customer transaction records from January 2023 to December 2024, the study applies a 3-point tertile scoring system to categorize customers into 10 distinct segments. The findings identify critical segments such as Sultan Internet (Champions 27 customers with perfect RFM scores of 333) and Juragan Kuota (Loyal Customers). Crucially, the analysis reveals a significant at-risk segment comprising high-value customers who have ceased transacting. Ethnographic analysis further reveals that high-value segments prioritize network stability characterized as fear of disconnection over price, whereas loyal segments place greater value on administrative simplicity. By integrating these insights, the research formulates a tailored Online Value Proposition (OVP) for each segment.