Applied Research On Marketing Data Of X-large Supermarkets Based On Data Mining

This article is based on the data collection of 66667 consumer records of a large supermarket organized by the Zero Dataway Company in the China Big Data Action Innovation Contest.It applies data mining to the excavation of commodity and customer characteristics in a large supermarket,from the consumer's consumption time preference to consumers.The analysis of category-related consumer relations,consumer-feature clustering,and the impact of promotions on consumer spending are conducted in four areas to explore the consumption status and internal rules of a large-scale supermarket,so as to provide targeted decision-making advice for supermarket marketing managers.Firstly,assumptions and data preprocessing are performed on the dataset;then the consumer's time preference is explored,and it is found that the weekend,workday,and Chinese New Year effects have a significant impact on the choice of consumer spending patterns;furtherly,this paper applies the Apriori algorithm to the monthly The analysis of association rules was performed on the products purchased by the consumers on the weekends and workdays,and then the cluster analysis was performed on the consumers using the K-Mean algorithm to classify the consumers according to their purchase patterns and consumption characteristics.At the same time,analyze the impact of promotion methods on consumer spending,consider holiday and weekend effects,establish a regression model of bulk product discounts on sales volume,and explore the sensitivity of sales volume to discounts.In the end,through the excavation of commodities and customer characteristics,this paper proposes targeted recommendations for supermarket marketing managers to sell from shopping baskets,consider weekend effects,establish membership systems,and improve false promotions,so as to better achieve Supermarket sustainable management and win the trust of consumers to provide scientific theoretical business guidance!...