电商平台用户行为分析系统研究

Research on User Behavior Analysis System of E-commerce Platform

随着互联网的快速发展,用户规模急剧增加,如何在海量数据中了解用户的消费和购物习惯成为电商平台激烈竞争中面临的严峻挑战。为了解决这一问题,笔者在GTK+和Pandas基础上研究了电商平台用户行为分析系统的多层次架构,并阐述各层级功能模块的实现方式,以此为电商平台定位优质客户和优化营销方式提供辅助支持。

With the rapid development of the Internet and the rapid increase in the number of users, how to understand users’ consumption and shopping habits in massive amounts of data has become a severe challenge faced by e-commerce platforms in the fierce competition. In order to solve this problem, the author studied the multi-level architecture of the user behavior analysis system of the e-commerce platform on the basis of GTK+ and Pandas, and explained the implementation methods of the functional modules at each level, so as to locate high-quality customers and optimize the marketing methods for the e-commerce platform. Provide auxiliary support.