IBM Watson Advertising Revolutionizes Brand Engagement By Delivering Personalized AI-Driven Marketing Experiences

Contemporary marketing methods need accuracy, customization, and immediate response. IBM Watson Advertising presents an innovative method for brand interaction via the use of artificial intelligence into advertising processes. The aim is to improve customer engagement via the use of natural language processing and machine learning to provide contextually relevant, data-informed marketing communications. IBM Watson's AI functionalities facilitate the examination of consumer intent, behavior, and sentiment across many platforms, enabling marketers to customize content dynamically. AI-driven personalization enhances the relevance and engagement of marketing, hence strengthening customer-brand interactions. This approach enhances campaign efficiency by reducing dependence on human targeting and facilitating automated decision-making on a scale. This model facilitates cross-channel consistency, adapts to real-time user inputs, and adheres to ethical AI norms in data management. The use of IBM Watson in marketing frameworks indicates a transition towards intelligent advertising systems that can adapt to changing customer demands. The methodology presents prospective opportunities for scalable, adaptive, and significant brand experiences across various digital landscapes.

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Published
2025-06-05
DOI
https://doi.org/10.1109/iccsp64183.2025.11089251
Primary Topic
Ethics and Social Impacts of AI
Type
article
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IBM Watson Advertising Revolutionizes Brand Engagement By Delivering Personalized AI-Driven Marketing Experiences

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Ethics and Social Impacts of AI
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IBM Watson Advertising Revolutionizes Brand Engagement By Delivering Personalized AI-Driven Marketing Experiences

Alif Al Hasan, P Sathyanathan, M. Muthulekshmi, R Monisha, Vamsi Krishna Eruvaram, R Dhineshkumar
article en

Abstract

Contemporary marketing methods need accuracy, customization, and immediate response. IBM Watson Advertising presents an innovative method for brand interaction via the use of artificial intelligence into advertising processes. The aim is to improve customer engagement via the use of natural language processing and machine learning to provide contextually relevant, data-informed marketing communications. IBM Watson's AI functionalities facilitate the examination of consumer intent, behavior, and sentiment across many platforms, enabling marketers to customize content dynamically. AI-driven personalization enhances the relevance and engagement of marketing, hence strengthening customer-brand interactions. This approach enhances campaign efficiency by reducing dependence on human targeting and facilitating automated decision-making on a scale. This model facilitates cross-channel consistency, adapts to real-time user inputs, and adheres to ethical AI norms in data management. The use of IBM Watson in marketing frameworks indicates a transition towards intelligent advertising systems that can adapt to changing customer demands. The methodology presents prospective opportunities for scalable, adaptive, and significant brand experiences across various digital landscapes.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Saint Joseph's College (US), Peoria Hospital (US), Birla Institute of Technology and Science - Hyderabad Campus (IN), St. Joseph's Institute of Technology (IN), Peoria campus of the University of Illinois System (US), Saveetha University (IN)
Openalex Percentile: Top 82%
Ethics and Social Impacts of AI
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