The Impact of Artificial Intelligence on Customer Personalization Strategies in E-Commerce

Jiayu Zhang

doi:10.54097/ckz2kz37

Authors

Jiayu Zhang

DOI:

https://doi.org/10.54097/ckz2kz37

Keywords:

Artificial Intelligence, E-Commerce, Customer Personalization, Personalized Recommendation, Algorithmic Decision-Making, User Experience

Abstract

With the rapid development of digital economy and the in-depth popularization of e-commerce, customer personalization has become a core competitive factor for e-commerce platforms to improve user stickiness and transaction conversion rates. Artificial Intelligence (AI), as a disruptive technological force, is reshaping the theoretical framework and practical path of e-commerce customer personalization strategies with its capabilities of massive data analysis, deep feature mining and intelligent decision-making. This paper explores the multi-dimensional impact of AI on e-commerce customer personalization strategies: first, it analyzes the inherent demand for AI-driven transformation of personalization strategies in the current e-commerce development stage, and sorts out the core AI technologies applied in the field of customer personalization. Second, it constructs the implementation framework of AI-based e-commerce customer personalization strategies, and expounds the optimization paths of personalized recommendation, personalized marketing and personalized service supported by AI. Finally, it discusses the practical challenges faced by the application of AI in e-commerce personalization, such as data privacy risks and algorithmic bias, and proposes targeted solution strategies and future research directions. This paper provides a systematic theoretical reference and practical implementation scheme for e-commerce enterprises to optimize customer personalization strategies with the help of AI technology, and has important guiding significance for the high-quality development of the e-commerce industry.

Downloads

Download data is not yet available.

References

[1] Liu, Y., & Wang, H. (2022). Research on E-Commerce Personalized Recommendation Model Based on Deep Learning. Journal of Computer Applications, 42(5), 1365-1371.

[2] Zhang, L., & Li, J. (2023). The Impact of Artificial Intelligence on E-Commerce Customer Experience and Purchase Intention. Journal of Business Research, 156, 113245.

[3] Chen, X., & Zhang, Q. (2021). Data Privacy Protection in AI-Based E-Commerce Personalization. China Information Security, 8, 78-81.

[4] Wang, J., & Zhao, Y. (2024). Research on Breaking the Information Cocoon Room of E-Commerce AI Recommendation. Journal of Library and Information Science in Agriculture, 36(2), 102-110.

[5] Li, M., & Hu, S. (2022). AI Application Barriers and Countermeasures for Small and Medium-Sized E-Commerce Enterprises. Modern Business, 18, 67-69.

[6] Brown, T. B., et al. (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems, 33, 1877-1901.

[7] Gupta, S., & Kumar, V. (2023). Omnichannel Personalization in E-Commerce: A Machine Learning Approach. Journal of Retailing and Consumer Services, 72, 103568.

[8] European Commission. (2021). AI Act: Proposal for a Regulation on Artificial Intelligence. Brussels: European Commission Publications Office.

[9] Ma, Z., & Liu, X. (2023). Generative AI in E-Commerce: Application Scenarios and Development Challenges. Digital Economy Research, 5, 45-53.

[10] Zhang, C., & Wang, L. (2022). Fairness Optimization of E-Commerce AI Recommendation Algorithm. Computer Engineering and Design, 43(10), 2789-2796.