Research on E-commerce User Portrait Construction and Optimization Path Based on K-means Clustering Algorithm

With the popularization and development of e-commerce, the user groups faced by enterprises engaged in e-commerce have become more extensive and complex. In order to help e-commerce enterprises better achieve precision marketing, improve user loyalty, and provide personalized services to users, this article uses K-means clustering algorithm to construct e-commerce user portrait. Firstly, the basic principle of user portrait construction and the principle of K-means clustering algorithm were introduced, and the specific application of K-means clustering algorithm in user portrait construction was elaborated in detail. Research has found that the user portrait constructed by the K-means clustering algorithm can assist e-commerce enterprises in understanding customer psychology, positioning consumer groups, grasping market demand, and creating targeted marketing solutions that meet the needs of different consumer groups.