基于数据挖掘的销售产品分析

Zhuofan Zhong, Sihan Wu, Runkang Yang, Yiming Qian
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引用次数: 0

摘要

随着互联网的普及和发展,线上销售正在逐步取代线下销售,在销售行业中占据主要地位。销售模式的转变也将是大宗商品企业面临的巨大挑战。分析和挖掘市场信息和消费者反馈已成为网络营销的关键。本文以2020年美国大学生数学建模竞赛数据为基础,主要运用相关分析、多元Logistic回归、自然语言处理等数学方法,对阳光公司在网络市场上推出销售的微波炉、吹风机、婴儿乳头等产品制定销售策略,并对客户反馈数据进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Sales Products Based on Data Mining
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.
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