Issue |
SHS Web Conf.
Volume 220, 2025
2025 2nd International Conference on Language Research and Communication (ICLRC 2025)
|
|
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Article Number | 03028 | |
Number of page(s) | 6 | |
Section | Cultural Communication, Brand Marketing, and Media Strategies | |
DOI | https://doi.org/10.1051/shsconf/202522003028 | |
Published online | 13 August 2025 |
Research on Personalized Marketing Strategies for Enterprises under the Background of Artificial Intelligence
School of Business Administration, Huaqiao University, Quanzhou, Fujian, 362000, China
* Corresponding author: 2216108040@stu.hqu.edu.cn
Nowadays, as society steps into the digital era, the development speed of artificial intelligence is astonishing, which has changed the dissemination pattern of traditional marketing. However, artificial intelligence still has some technical limitations. This article focuses on the personalized marketing strategies of enterprises in the context of artificial intelligence, mainly discussing how enterprises can utilize artificial intelligence technology to achieve precise, efficient, and consumer-demand-aligned marketing dissemination results. This article concludes that artificial intelligence can precisely understand user profiles through big data analysis, thereby conducting personalized customization for product content. Subsequently, it implements precise push to enhance marketing efficiency, and the return on investment ratio has also improved. However, the application of artificial intelligence also faces challenges, such as data privacy and algorithm bias. Based on this, this article makes the following suggestions: enterprises need to do a good job in data management and risk prevention in advance. They should apply artificial intelligence technology more reasonably and optimize marketing strategies to make brands more competitive and promote the sustained and stable development of marketing dissemination.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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