Tartila, Hikmata (2025) Analisis Segmentasi Pelanggan Produk Haircare dengan Metode RFM pada Data Distribusi PT Triple One Global. Project Report (Praktek Kerja Lapang dan Magang). Faculty of Computer Science Department of Data Science. (Unpublished)
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Abstract
In the digital era, customer data utilization has become a crucial aspect of business strategy, including in the distribution of consumer products. PT Triple One Global, as a data and technology service provider, initiated customer segmentation for haircare products to improve the effectiveness of marketing strategies among its distribution partners. This project aims to classify customers based on purchasing behavior using the Recency, Frequency, and Monetary (RFM) method as the foundation for segmentation. The analysis was conducted on more than 17,000 customer transaction records from distribution partners over the period of September 2024 to March 2025. The methodology includes transaction data processing, RFM scoring, and categorization of customers into five main segments: Best Customer, Loyal Customer, Big Spender, At Risk, and Need Attention. This project also integrates interactive visualizations using Power BI to support real-time monitoring and informed decision-making for stakeholders. The results show that 63.56% of customers fall into low-engagement segments, requiring targeted retention strategies, while the remaining 36% are high-value customers who should be retained through loyalty programs. This segmentation has a significant impact in helping PT Triple One Global’s distribution partners gain deeper insights into customer behavior, design more targeted marketing approaches, and increase the efficiency of data-driven campaigns. Moving forward, it is recommended that the company continues to develop cross-product data integration and explore advanced segmentation techniques to enhance its competitiveness through analytics.
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang dan Magang)) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.6 Computer Programming | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||
| Depositing User: | hikmata tartila | ||||||||
| Date Deposited: | 21 May 2026 06:27 | ||||||||
| Last Modified: | 21 May 2026 06:27 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/51984 |
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