基于KMeans的多维度量化智能选品决策方法研究  

Research on Multi-dimensional Quantitative of Product Selection Decision Making Method with Intelligent Based on KMeans

作　　者：李光伟 秦锦飞 黄俊[2] LI Guang-wei;QIN Jin-fei;HUANG Jun(School of Economic and Management,Southwest University of Science and Technology,Mianyang 621010,China;School of Computer Science and Technology,Southwest University of Science and Technology,Mianyang 621010,China)

机构地区：[1]西南科技大学经济管理学院,四川绵阳621010 [2]西南科技大学计算机科学与技术学院,四川绵阳621010

出　　处：《计算机技术与发展》2025年第3期194-201,共8页Computer Technology and Development

基　　金：西南科技大学教改项目(22xn0053);四川省自然科学基金项目(2022NSFSC0894)。

摘　　要：针对传统跨境电商卖家选品方法存在过分依赖经验和个人判断而缺乏科学与系统性依据的问题,提出了一种基于亚马逊平台销售数据的多维度系数聚类选品方法。该方法利用大数据挖掘技术揭示隐藏在市场数据中的选品依据,从有销售历史的商品集合中筛选出具备广泛市场接受度、竞争压力小、质量有保障的优质商品,帮助卖家更加科学地进行商品选择。以亚马逊平台的篮球类目为例进行了实证分析,通过评论数、商品数、竞争指数、市场规模占比、消费者平均评分、热销商品比例构建了数据分析指标;利用KMeans聚类分析法分别对品牌、适用人群、制作材料、价格四个维度的销售情况进行了分析,总结各个维度的推荐信息,并对案例选品结果进行了为期三个月的跟踪取证。结果表明,该方法决策的目标商品的销售表现良好,证明了选品方法的有效性,为跨境电商卖家建立起一种科学、系统、数据驱动的销售商品决策工具。Considering the issue of traditional product selection methods for cross-border e-commerce sellers being overly reliant on experience and personal judgment,and lacking a scientific and systematic basis,a multi-dimensional coefficient clustering product selection method is proposed,which is based on sales data from the Amazon platform.This method leverages big data mining technology to uncover the hidden basis for product selection within market data.It enables the selection of high-quality products that possess broad market acceptance,low competitive pressure,and assured quality from a collection of products with a sales history,thereby facilitating more scientific product choices for sellers.An empirical analysis was carried out using the basketball category on the Amazon platform as an example.In this analysis,data analysis indicators were constructed based on the number of reviews,number of products,competition index,market size proportion,average consumer rating,and proportion of best-selling products.The KMeans clustering analysis method was employed to analyze sales data across four dimensions:brand,target audience,material,and price.Recommended information for each dimension was summarized,and the product selection results were monitored over a period of three months.The findings indicate that the target products selected by the proposed method have demonstrated strong sales performance,thereby validating the effectiveness of the product selection method.This offers cross-border e-commerce sellers with a scientific,systematic,and data-driven tool for making sales product decisions.

关 键 词：跨境电商 多维度量 智能选品 KMeans聚类 销售决策 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]