ArticleOpen Access http://dx.doi.org/10.26855/acc.2025.10.016
Research on Intelligent Marketing Strategy Optimization Based on Generative AI and User Behavior Prediction
Jiazhen Zhu
Stern School of Business, NYU, New York, NY 10012, USA.
*Corresponding author: Jiazhen Zhu
Published: November 05, 2025
Abstract
With the acceleration of digital transformation, traditional marketing methods can no longer meet the needs of enterprises. Generative artificial intelligence (AI) and user behavior prediction offer new opportunities for smart marketing. This study explores how the combination of these two technologies can optimize marketing strategies by analyzing the theoretical foundations of generative AI and user behavior prediction. Through the case study of Brand A, an optimized path based on data collection, behavior analysis, personalized recommendations, and dynamic feedback is proposed. The results show that the combination of these technologies significantly improves marketing accuracy and execution, particularly in terms of enhancing user experience and conversion rates, providing important references for practical applications in the field of smart marketing.
Keyword
Artificial Intelligence; User Behavior; Marketing Strategy; Smart Optimization
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Copyright
© 2025 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
https://creativecommons.org/licenses/by-nc-nd/4.0/
How to cite this paper
Research on Intelligent Marketing Strategy Optimization Based on Generative AI and User Behavior Prediction
How to cite this paper: Jiazhen Zhu. (2025) Research on Intelligent Marketing Strategy Optimization Based on Generative AI and User Behavior Prediction. Advances in Computer and Communication, 6(4), 250-255.
DOI: http://dx.doi.org/10.26855/acc.2025.10.016