Revolutionizing Marketing: How Ai is Transforming Customer Engagement

Abhishek Raghulan () and N. Jayanthi
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Abhishek Raghulan: T. John College, Associate Professor (MBA Department)
N. Jayanthi: Assistant Professor (MBA Department), Vels Institution of Science Technology & Advanced Studies (VISTAS)

A chapter in Proceedings of the International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024), 2024, pp 478-492 from Springer

Abstract: Abstract This paper digs into the progressive effect of Man-made brainpower (simulated intelligence) on the scene of promoting and its significant ramifications for client commitment. AI's integration into marketing strategies has ushered in a paradigm shift, redefining how businesses interact with and understand their customer base. Through an in-depth exploration of AI-powered tools and their application in marketing, this study illuminates the transformative potential of AI in driving personalized, data-driven customer experiences. By analysing AI-driven innovations across various marketing domains, from predictive analytics to chatbots and recommendation systems, this paper elucidates the pivotal role of AI in enhancing customer engagement. Total data collected during 2013 to 2023 is 28, 893. But during 2023 majority of the author published their article using AI software. It was found that major countries using this AI software in the marketing field is China and Australia because most of the authors published their article from these countries only. Furthermore, it discusses the challenges and opportunities presented by AI adoption in marketing, emphasizing the need for ethical considerations and strategic implementation for maximum impact. Ultimately, this paper underscores AI's pivotal role in reshaping marketing practices, enabling businesses to forge deeper connections and cultivate enduring relationships with their audience in the digital age.

Keywords: Artificial Intelligence; Marketing; Customer Engagement; Personalization; Data-driven Strategies; AI-powered Tools; Predictive Analytics (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-433-4_36

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