Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations

作     者：Aghaei, Raha Kiaei, Ali A. Boush, Mahnaz Vahidi, Javad Zavvar, Mohammad Barzegar, Zeynab Rofoosheh, Mahan 

作者机构：School of Mathematics and Computer Science Iran University of Science & Technology Tehran Iran Department of Artificial Intelligence in Medicine Faculty of Advanced Technologies in Medicine Iran University of Medical Sciences Tehran Iran Cellular and Molecular Biology Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Computer Engineering Sari Branch Islamic Azad University Sari Iran Computer engineering group Alborz Vocational Technical University Alborz Iran 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2025年

核心收录：

主　　题：Sales 

摘      要：Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation in marketing management. In this paper, we explore the transformative potential of LLMs along with the current applications, future directions, and strategic recommendations for marketers. In particular, we focus on LLMs major business drivers such as personalization, real-time-interactive customer insights, and content automation, and how they enable customers and business outcomes. For instance, the ethical aspects of AI with respect to data privacy, transparency, and mitigation of bias are also covered, with the goal of promoting responsible use of the technology. Through best practices and the use of new technologies businesses can tap into the LLM potential, which help growth and stay one step ahead in the turmoil of digital marketing. This article is designed to give marketers the necessary guidance by using best industry practices to integrate these powerful LLMs into their marketing strategy and innovation roadmap without compromising on the ethos of their brand. Copyright © 2025, The Authors. All rights reserved.