Analysis of Sales Products Based on Data Mining

Zhuofan Zhong, Sihan Wu, Runkang Yang, Yiming Qian


With the popularization and development of the Internet, online sales are gradually replacing offline sales and occupy a major position in the sales industry. The transformation of sales mode will also be a huge challenge for commodity companies. Analyzing and mining market information and consumer feedback has become the key to network marketing. Based on the data of mathematical modeling competition for American college students in 2020, this paper mainly uses mathematical methods such as correlation analysis, multiple Logistic regression and natural language processing to formulate sales strategies for microwave ovens, hair dryers and baby nipples launched and sold by Sunshine Company in the online market, and analyze customer feedback data.


Correlation Analysis; Multinomial Logistic Regression; EWM

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DOI: https://doi.org/10.18282/ff.v11i2.3044


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