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Kyobo Book Center Customer Segmentation Using K-means Cluster Analysis

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In this study, we explored the integration of the Kyobo Book Center and its subsidiary Hottracks into a single corporation, focusing on the unified management of customer data that was previously managed independently by each entity. Our research aimed to identify new customer types and develop effective marketing strategies from the perspective of the consolidated Kyobo Book Center. We conducted customer segmentation by merging data from over 5 million members in 2022 and analyzing the characteristics of the segmented clusters. The process involved refining and transforming the data to align it with the perspective of the integrated Kyobo Book Center. Subsequently, we employed k-means cluster analysis to examine customer clusters in detail. This approach is anticipated to provide a competitive advantage by identifying the distinct characteristics of each cluster, allowing for the optimization of products and services for specific, segmented customer groups. Implementating marketing strategies based on customer segmentation is expected to enhance the customer experience and boost sales significantly. This strategy will provide a new paradigm for future corporate management, emphasizing the importance of tailored marketing in today’s competitive marketplace.

Abstract

In this study, we explored the integration of the Kyobo Book Center and its subsidiary Hottracks into a single corporation, focusing on the unified management of customer data that was previously managed independently by each entity. Our research aimed to identify new customer types and develop effective marketing strategies from the perspective of the consolidated Kyobo Book Center. We conducted customer segmentation by merging data from over 5 million members in 2022 and analyzing the characteristics of the segmented clusters. The process involved refining and transforming the data to align it with the perspective of the integrated Kyobo Book Center. Subsequently, we employed k-means cluster analysis to examine customer clusters in detail. This approach is anticipated to provide a competitive advantage by identifying the distinct characteristics of each cluster, allowing for the optimization of products and services for specific, segmented customer groups. Implementating marketing strategies based on customer segmentation is expected to enhance the customer experience and boost sales significantly. This strategy will provide a new paradigm for future corporate management, emphasizing the importance of tailored marketing in today’s competitive marketplace.

참고문헌 (8)

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  8. Oliveira GV, "Improving k-means through distributed scalable metaheuristics", Neurocomputing, 246, pp.45~57 (2017)

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