Penerapan rfm analysis pada customer profiling menggunakan k-means clustering

Nathasya, Celine (2022) Penerapan rfm analysis pada customer profiling menggunakan k-means clustering. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

The development of information technology causes an explosion in the amount of data, yet the data must be processed in order to obtain useful insights. The use of data is needed to study the needs, behaviour, and customer's value are meant to build better relationships or what is often referred to Customer Relationship Management (CRM). As the company grows, data is getting abundant and more difficult to interact directly with customers and problems such as marketing campaigns that are less effective can result in losses if not immediately addressed. Therefore, customer segmentation was carried out using recency, frequency, and monetary (RFM) as variables and K-Means clustering by determining the number of clusters using the elbow method and silhouette score. Based on the analysis results, there are three types of clusters, categorized as best customers, may not lost customers, and average customers./Perkembangan teknologi informasi menyebabkan ledakan jumlah data, namun data tersebut harus diolah agar mendapatkan wawasan yang dapat digunakan. Pemanfaaatan data diperlukan untuk mempelajari kebutuhan, perilaku, dan nilai dari customer untuk membangun relasi yang lebih baik dengan mereka atau yang sering disebut sebagai customer relationship management (CRM). Seiring berkembangnya perusahaan, data semakin banyak dan semakin sulit untuk melakukan interaksi langsung dengan customer dan adapun persoalan seperti kampanye pemasaran yang kurang efektif sehingga dapat berakibat kerugian apabila tidak segera diatasi. Oleh karena itu, dilakukan segmentasi customer menggunakan variabel recency, frequency, dan monetary (RFM) dan mengimplementasikan K-Means clustering dengan penentuan jumlah cluster menggunakan metode elbow dan silhouette score. Berdasarkan hasil analisa, terdapat tiga jenis cluster yang dikategorikan sebagai best customer, may not lost customer, dan average customer.

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