Segmenting Potential Customers with Kohonen Network: A Banking Sector Case Study

Küçük Resim Yok



Dergi Başlığı

Dergi ISSN

Cilt Başlığı


Springer Science and Business Media Deutschland GmbH

Erişim Hakkı



The main objective of this paper is to understand the characteristics of the new customers of a web-based lending bank via a segmentation methodology with Kohonen Network. The main problem involved here is the proposition of a data-driven segmentation approach in the prevention of the loss of remunerative customers’ acquisition in the digital era’s banking industry. The reason for choosing Kohonen Network is the ability to work on large volumes of data and the most appropriate determination of the cluster number, which is the most important decision for cluster analysis, by the technique itself. The well-known purpose of cluster analysis in business analytics is to provide the necessary foresight by revealing previously unknown critical customer characteristics and degrees of importance in order to assist the business in charge in strategic marketing decisions such as market segmentation and target market selection. As a result of the study, new marketing strategies regarding the loss of new customers’ acquisition suggested through the findings of Kohonen clusters. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.


European, Asian, Middle Eastern, North African Conference on Management and Information Systems, EAMMIS 2021 -- 19 March 2021 through 20 March 2021 -- -- 260709

Anahtar Kelimeler

Clustering, Data mining, Kohonen network, Lending bank, Market segmentation


Lecture Notes in Networks and Systems

WoS Q Değeri

Scopus Q Değeri



239 LNNS