概述人工智能及其在营销中的应用,重点是大型语言模型

Reza Amini, Ali Amini
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引用次数: 0

摘要

物联网、大数据分析、区块链和人工智能(AI)等新兴技术极大地改变了企业的运营。在这些技术中,人工智能是最新的、最具影响力的技术,它彻底改变了营销实践。全球专业人士都在积极寻求适合其营销需求的人工智能解决方案。对现有文献进行系统回顾,可以突出人工智能在市场营销中的重要性,并揭示未来的研究路径。将大数据源和人工智能工具整合到营销实践中,代表了对传统方法的突破,开创了营销教育的新时代。本文探讨了人工智能在市场营销领域的最新进展,重点介绍了这些发展如何使从业人员有效地浏览和利用广泛而复杂的数据集进行预测分析。通过整合大数据和人工智能,营销战略现在可以直接与执行保持一致,从而加强战略规划和营销成果预测。然而,采用这些技术需要向适应性学习方法转变,超越传统的评估方法,以更好地适应当今营销环境的动态性质。向大数据和人工智能驱动的方法过渡,使专家们能够应对现代营销环境不断变化的需求。这种转变超越了传统的分析方法,利用了大语言模型等尖端人工智能技术,并通过角色扮演模拟等创新学习体验提高了大数据的利用率。这种整合不仅拓宽了营销人员的分析能力,还促进了对数据驱动决策的身临其境和体验式理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An overview of artificial intelligence and its application in marketing with focus on large language models
Emerging technologies like the Internet of Things, big data analytics, blockchain, and artificial intelligence (AI) have significantly transformed business operations. Among these, AI stands out as the most recent and impactful, revolutionizing marketing practices. Professionals globally are actively seeking AI solutions tailored to their marketing needs. A systematic review of existing literature can highlight AI's significance in marketing and reveal future research pathways. Integrating big data sources and AI tools into marketing practices represents a departure from traditional methods, ushering in a new era of marketing education. This paper explores recent advancements in AI within the marketing sector, highlighting how these developments enable practitioners to effectively navigate and utilize extensive and complex datasets for predictive analytics. By integrating big data and AI, marketing strategies can now be directly aligned with execution, enhancing both strategic planning and the forecasting of marketing outcomes. However, the adoption of these technologies necessitates a shift towards adaptive learning approaches, moving beyond traditional assessment methods to better accommodate the dynamic nature of today's marketing environment. The transition to big data and AI-driven approaches equips experts for the evolving demands of the modern marketing landscape. This shift transcends traditional analytics by leveraging cutting-edge AI technologies, such as Large Language Models, and enhances the utilization of big data through innovative learning experiences, such as role-playing simulations. This integration not only broadens the analytical capabilities of marketers but also fosters a more immersive and experiential understanding of data-driven decision-making.
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