A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting

Yıl 2025, Cilt: 25 Sayı: 3, 212 - 229, 25.09.2025

Bahar Taşar

https://doi.org/10.18037/ausbd.1594874

Öz

Customer segmentation allows companies to create mutual profiles of their customers. Determining industrial customer segments based on a single perspective causes various customer features to be disregarded. This study aims to develop a holistic segmentation approach in a B2B setting. The paper proposes a multi-dimensional segmentation model with four main criteria: customer purchasing performance, customer cooperation, customer workload, and customer potential. The case study demonstrates the real-life application of the proposed model using 379 customer data and 17 sub-criteria under four dimensions. The Fuzzy C-Means Clustering Algorithm creates the customer segments, and the Fuzzy Analytical Hierarchical Process is used to calculate criteria weights. The marketing strategies of each segment are used to guide customer relations and managerial decisions. This paper suggests that companies segment their customers by considering financial performance, cooperation level, future potential throughput, and challenges. It provides a practical and holistic insight into industrial customer segmentation.

Anahtar Kelimeler

Customer segmentation , industrial customer relations , fuzzy analytic hierarchy process , fuzzy C-means algorithm

Bulanık C-Ortalamalar Kümeleme Algoritmasını Kullanan Çok Boyutlu Bir Müşteri Segmentasyon Modeli: B2B Ortamında Bir Pilot Çalışma

Öz

Müşteri segmentasyonu, işletmelerin müşterilerinin ortak profillerini oluşturmalarına olanak tanır. Endüstriyel müşteri segmentlerinin tek bir bakış açısına göre belirlenmesi, çeşitli müşteri özelliklerinin göz ardı edilmesine neden olmaktadır. Bu çalışma, B2B ortamında bütünsel bir segmentasyon yaklaşımı geliştirmeyi amaçlamaktadır. Çalışmada dört ana kriter içeren çok boyutlu bir segmentasyon modeli önerilmektedir: müşteri satın alma performansı, müşteri işbirliği, müşteri iş yükü ve müşteri potansiyeli. Vaka çalışması, 379 müşteri verisi ve dört boyut altında 17 alt kriter kullanarak önerilen modelin gerçek hayattaki uygulamasını göstermektedir. Bulanık C-Ortalamalar Kümeleme Algoritması müşteri segmentlerini oluşturmakta ve kriter ağırlıklarını hesaplamak için Bulanık Analitik Hiyerarşik Süreç kullanılmaktadır. Her bir segmentin pazarlama stratejileri, müşteri ilişkilerini ve yönetimsel kararları yönlendirmek için kullanılır. Bu çalışma, işletmelerin finansal performans, işbirliği düzeyi, gelecekteki potansiyel iş hacmi ve zorlukları dikkate alarak müşterilerini segmentlere ayırmaları gerektiğini öne sürmektedir. Endüstriyel müşteri segmentasyonuna pratik ve bütüncül bir bakış açısı sağlamaktadır.

Anahtar Kelimeler

Müşteri segmentasyonu , endüstriyel müşteri ilişkileri , bulanık analitik hiyerarşi süreci , bulanık C-means algoritması

Kaynakça

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