Vegetable Merchandise Analysis from a Quarterly Sales Data Perspective
DOI:
https://doi.org/10.54097/8e7wb791Keywords:
Kendall correlation analysis, normality tests, visualizing sales changes, big data.Abstract
In the field of fresh vegetable retailing, the category diversity and time-sensitive characteristics of commodities pose unique challenges to inventory management and pricing decisions. Comprehensively analyzing the distribution pattern of sales volume of different categories and individual items of vegetable commodities and their interrelationships is of great significance to retailers' scientific replenishment and pricing decisions. By categorizing vegetable sales every quarter, a comprehensive analysis is carried out on a category and individual item basis. Visualization was used to show the distribution pattern of sales volume by category and individual item. Subsequently, Kendall correlation analysis was utilized to explore the relationship between the sales volume of different vegetable categories. In addition, the interrelationships between the sales volumes of different vegetable individual items were investigated in conjunction with waterfall diagrams. Through in-depth analysis of sales data, understanding the sales relationship between different vegetable categories can help retailers develop a more refined pricing strategy, make pricing adjustments based on the relative sales of goods, and improve sales revenue and profit levels. Such scientific inventory management and pricing strategies not only help meet customer demand and enhance customer experience, but also strengthen customer loyalty and promote long-term stable business development.
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