Stationery stores are retail stores that sell all kinds of necessary office and school equipment, such as writing paper, envelopes, paint, musical instruments, etc. The problem in this store is that consumers are still looking for the goods to buy, and the goods are not arranged neatly. This increases the chance of consumers not buying other desired products because the structure of these products is unclear and invisible. On this basis, it is necessary to redesign the layout based on the existing transaction data of consumers. This article uses a data-driven method based on data basket technology, which is a data mining technology that can identify the strength of association between paired products purchased together, and can identify when two or more things happen at the same time co-occurrence model. The goal is to develop an effective analysis method to solve the actual stationery layout based on consumer behaviour. According to the calculation results, the market shopping basket analysis method determines that the products that are allowed to be purchased on an impulse are school stationery, drawing tools and painting tools, and these products prove that they have the minimum mutual influence specified threshold. Then, by using the activity diagram to identify the proximity level between all the paired product categories, the suggested layout is generated. Therefore, these suggested layouts can greatly help the store obtain greater sales growth from the highest sales, and can help sell music products with media and decorative categories.

Topics
Musical instruments, Data mining, Schools
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