Asia Marketing Journal | 2026
Authors: Oh H.R.; Cheong Y.
DOI: 10.53728/2765-6500.1674
Journal: Asia Marketing Journal
Year: 2026
Publisher: Korean Marketing Association
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 0
This study clusters consumers according to their hourly online shopping consumption patterns and develops optimized advertising strategies that can be practically applied by companies. Specifically, we considered multidimensional variables related to consumers, including demographic characteristics, shopping frequency, information search and content consumption characteristics, and lifestyle traits. We explored consumer types by comparing various clustering algorithms and applying the optimal clustering method for each time period. The analysis results show significant differences in payment amounts according to payment time periods. Regarding consumer types, consumption tendencies are distinctly differentiated by payment time periods, with each cluster showing different characteristics. This study is significant in that it makes a practical contribution to optimizing marketing activities by time period by establishing advertising strategies tailored to changing consumer characteristics and more efficiently allocating advertising budgets through consumer segmentation based on actual payment data. © 2026 Korean Marketing Association (KMA).
Clustering analysis; Consumer segmentation; Hierarchical clustering; K-means; Online shopping