Paper
16 January 2025 Sales data analysis and product layout analysis model based on association rule mining algorithm
Chunying Xia, YingYing Ma
Author Affiliations +
Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134474O (2025) https://doi.org/10.1117/12.3045746
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China
Abstract
This study uses association rule mining algorithms to conduct in-depth analysis of sales data of retail enterprises, aiming to reveal the purchasing patterns and correlations between products. By analyzing the transaction records of supermarkets, this study identified multiple frequently purchased product combinations and proposed targeted product layout strategies based on these findings. These strategies include neighboring placement of interrelated products, bundled promotions, and inventory management optimization. The preliminary results after implementation indicate that these data-driven layouts and promotional strategies have effectively improved sales and customer satisfaction. This study not only demonstrates the practical application of association rule mining in the retail industry, but also provides a new perspective for retail enterprises to utilize sales data and optimize business operations. Finally, this article also discusses the limitations of the research and proposes possible directions for future research.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Chunying Xia and YingYing Ma "Sales data analysis and product layout analysis model based on association rule mining algorithm", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134474O (16 January 2025); https://doi.org/10.1117/12.3045746
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KEYWORDS
Mining

Data analysis

Analytical research

Industrial applications

Statistical analysis

Data modeling

Detection and tracking algorithms

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