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

Year: 2025

Type: conference-paper

Abstract: 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.

Source: International Conference on Computer Information and Big Data Applications (CIBDA)

DOI: 10.1145/3746709.3746946

Authors: Xiwang Cheng, Kang Le, Zihao Zhou, Xiangmin Xu

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4413812566

FWCI:

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