Pos Aja Customer Segmentation at the Yogyakarta Post Office Using the RFM (Recency, Frequency, Monetary) Method

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Wirasta Catur Pambudi
Syukron Abdul Aziz
Roro Anteng

Abstract

Every business must continue to innovate due to the industry's rapid evolution if it hopes to avoid being disrupted by innovations in the future. The Pos Aja! app, a revolutionary new offering from courier and logistics services provider Pos Indonesia, was introduced in 2020. With Just Post!, consumers can transact from anywhere without physically visiting the post office. Pos Aja! facilitates not just transaction processing for clients but also helps businesses better understand their clientele. The technique known as customer relationship management, or CRM, works to maintain and improve ties between businesses and their clients. Client segmentation is one method of investigating client profiles. Recency, Frequency, and Monetary analysis, or RFM, is the customer segmentation method employed in this study in order to identify the traits of Pos Aja! customers. Three types of Pos Aja! customers—Gold, with 857 clients; Silver, with 566 customers; and Bronze, with 688 customers—were obtained based on the RFM data. The RFM data were then sorted to determine the category of new Pos Aja! clients. The Random Forest, Decision Tree, and Support Vector Machine (SVM) classification techniques are employed. With an accuracy level of 96.69%, the SVM model emerged as the top performer among these three models. Therefore, the SVM model can be applied to determine new client groups.

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References

I-Cheng Yeh, King-Jang Yang, and Tao-Ming Ting. “Knowledge discovery on RFM model using Bernoulli sequence”. In: Expert Systems with Applications 36.3 (2009), pp. 5866–5871