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

Cilt: 25 Sayı: 3 25 Eylül 2025
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A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting

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

Kaynakça

  1. Barrera, F., Segura, M., & Maroto, C. (2024). Multiple criteria decision support system for customer segmentation using a sorting outranking method. Expert Systems with Applications, 238, Part F, 122310.
  2. Bayer, J. (2010). Customer segmentation in the telecommunications industry. Journal of Database Marketing and Customer Strategy Management, 17(3-4), 247–256.
  3. Berger, P.D, & Nasr, N.I. (1998). Customer Lifetime Value: Marketing Models and Applications. Journal of Interactive Marketing, 12(1), 17–29.
  4. Bezdek, J.C. (1981), Pattern Recognition with Fuzzy Objective Function Algorithms, Springer New York.
  5. Bonner, J.M, & Walker, O.C. (2004). Selecting Influential Business-to-Business Customers in New Product Development: Relational Embeddedness and Knowledge Heterogeneity Considerations. Journal of Product Innovation Management, 21(3), 155–169.
  6. Bošnjak, Z, & Grljevic, O. (2011). Credit Users Segmentation for improved Customer Relationship Management in Banking. 6th I EEE International Symposium on Applied Computational Intelligence and Informatics, 379- 384.
  7. Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233-247.
  8. Casas‐Rosal, J. C., Segura, M., & Maroto, C. (2021). Food market segmentation based on consumer preferences using outranking multicriteria approaches. International Transactions in Operational Research, 30(3), 1537-1566..

Ayrıntılar

Birincil Dil

İngilizce

Konular

Endüstriyel Pazarlama

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

25 Eylül 2025

Gönderilme Tarihi

2 Aralık 2024

Kabul Tarihi

26 Nisan 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 25 Sayı: 3

Kaynak Göster

APA
Taşar, B. (2025). A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(3), 212-229. https://doi.org/10.18037/ausbd.1594874
AMA
1.Taşar B. A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting. AÜSBD. 2025;25(3):212-229. doi:10.18037/ausbd.1594874
Chicago
Taşar, Bahar. 2025. “A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting”. Anadolu Üniversitesi Sosyal Bilimler Dergisi 25 (3): 212-29. https://doi.org/10.18037/ausbd.1594874.
EndNote
Taşar B (01 Eylül 2025) A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting. Anadolu Üniversitesi Sosyal Bilimler Dergisi 25 3 212–229.
IEEE
[1]B. Taşar, “A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting”, AÜSBD, c. 25, sy 3, ss. 212–229, Eyl. 2025, doi: 10.18037/ausbd.1594874.
ISNAD
Taşar, Bahar. “A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting”. Anadolu Üniversitesi Sosyal Bilimler Dergisi 25/3 (01 Eylül 2025): 212-229. https://doi.org/10.18037/ausbd.1594874.
JAMA
1.Taşar B. A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting. AÜSBD. 2025;25:212–229.
MLA
Taşar, Bahar. “A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting”. Anadolu Üniversitesi Sosyal Bilimler Dergisi, c. 25, sy 3, Eylül 2025, ss. 212-29, doi:10.18037/ausbd.1594874.
Vancouver
1.Bahar Taşar. A Multi-Dimensional Customer Segmentation Model Using The Fuzzy C-Means Clustering Algorithm: A Pilot Study In The B2B Setting. AÜSBD. 01 Eylül 2025;25(3):212-29. doi:10.18037/ausbd.1594874

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