| Summary: | Intelligent and strategic product arrangements in retail stores can increase sales and maximize profits. However, shelf operations management is increasingly challenging with a large variety of products available on limited retail shelf space, incurring what is commonly known as the shelf space allocation problem (SSAP). Retailers must plan shelf space by considering two factors, namely appropriate allocation of products on shelves and customer preferences. From the customer shopping behavior analysis, this research aims to redesign retail planograms based on product allocation on priority display shelf space by applying a merchandising decision model. Multilevel association rule mining was used to determine the relationship between categories, subcategories, and product items by utilizing customer shopping basket data. The study presented is a planogram design for priority display shelves based on customer preferences, which can be implemented to maximize profits for retailers and increase consumer satisfaction. © 2024, Prince of Songkla University. All rights reserved.
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