Güncellik Sıklık Parasallık Modeline Dayalı Müşteri Bölümlendirme: E-Perakende Sektöründe Bir Uygulama

Pazarlama alanındaki çalışmalarda, yoğun rekabet ile başa çıkmaya çalışan işletmeler açısından müşterilerin önemine sıklıkla dikkat çekildiği görülmektedir. Pazarlama yönetimi bağlamında öne çıkan bir yaklaşım olan Müşteri İlişkileri Yönetimi (MİY), işletmeler ile müşterileri arasında kurulan ilişkilerin geliştirilmesini amaçlamaktadır. Müşteri verisinin işletme ve müşterileri için değer yaratmak üzere analiz edilmesi, MİY’in uygulamada gereksinimlerinden birisi olarak ifade edilebilir. Bu bağlamda müşteri bölümlendirme, benzer niteliklere sahip müşteri gruplarının ortaya çıkarılarak grup odaklı pazarlama stratejilerinin uyarlanması için yararlı bir işlev görmektedir. Müşteri bölümlendirme için ortaya konulmuş çeşitli yaklaşımlar arasında RFM Modeli, etkin ve kolay uyarlanabilir olmasıyla öne çıkmaktadır. Müşterilerin satış verisine ilişkin 3 farklı boyut üzerinden sıralanmasına dayanan yöntem, sıralamada kullanılan puanlama biçimine göre çeşitli yaklaşımlara konu olmaktadır. Bu çalışmada, RFM yöntemini iki farklı puanlama yaklaşımı ile yürütmek üzere geliştirilmiş bir prototip yazılım tanıtılmaktadır. Bir e-perakende işletmesinden alınan satış verisi sözü edilen yazılım ile incelenmiş, RFM modeline ilişkin her iki puanlama yöntemi ile bölümlendirme yapılmış, bulgular veri madenciliği bağlamında değerlendirme ölçütleri ile karşılaştırılmıştır. Son olarak ortaya çıkarılan müşteri bölümleri sunulmuş ve seçilen gruplara yönelik öneriler sıralanmıştır.

Customer Segmentation Based On Recency Frequency Monetary Model: A Case Study in E-Retailing

Marketing studies have often drawn attention to the importance of customers for businesses that aim to endure in a harsh competitive environment. Customer Relationship Management (CRM) has been a prominent approach in marketing management that aims to improve relationships with customers. A practical implication of the CRM approach is the analysis of customer data to extract value for businesses, as well as customers. In this context, customer segmentation has been a useful task that helps to group customers with similar attributes and designate better-tailored marketing strategies for customer groups. Among a variety of approaches for customer segmentation, Recency Frequency Monetary (RFM) Model stands out as an easy-to-adopt and effective technique. Based on three dimensions regarding the sales data, the RFM Model depends on scoring customers with different approaches. In this study, a prototype software is introduced that helps to apply the RFM technique with two scoring approaches. Moreover, the sales data obtained from an e-retailer has been analyzed for clustering using the prototype software, and clusters discovered with RFM variants were compared using cluster evaluation metrics. Finally, the segments were presented along with relevant offers for marketing strategies.

Keywords:

Customer Segmentation, RFM Model Analytical CRM,

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