When AI meets store layout design: a review
作者:Kien Nguyen, Minh Le, Brett Martin, Ibrahim Cil, Clinton Fookes
摘要
An efficient store layout presents merchandise to attract customer attention and encourages customers to walk down more aisles which exposes them to more merchandise, which has been shown to be positively correlated with the sales. It is one of the most effective in-store marketing tactics which can directly influence customer decisions to boost store sales and profitability. The recent development of Artificial Intelligence techniques, especially with its sub-fields in Computer Vision and Deep Learning, has enabled retail stores to take advantage of existing CCTV infrastructure to extract in-store customer and business insights. This research aims to conduct a comprehensive review on existing approaches in store layout design and modern AI techniques that can be utilized in the layout design task. Based on this review, we propose an AI-powered store layout design framework. This framework applies advanced AI and data analysis techniques on top of existing CCTV video surveillance infrastructure to understand, predict and suggest a better store layout.
论文关键词:Video analytic, CCTV visual intelligence, Business intelligence, Store layout, Retail layout
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10462-022-10142-3