Artificial Intelligence in Product Management: Enhancing User Experience Personalization through GenAI

In today’s digital age, personalized customer experiences are crucial for businesses to thrive. Traditional methods of customer experience personalization often rely on static models that struggle to adapt to dynamic consumer behaviors and preferences. This research study proposes a novel dynamic integrated model that leverages Generative AI to continuously update and refine customer experiences. By analyzing multi-dimensional data sources such as transaction history, online interactions, and social media activity, the model can capture the evolving nature of customer preferences. This research study explores the potential of integrating advanced algorithms like Generative Adversarial Networks (GANs) and Large Language Models (LLMs) to generate personalized content, recommendations, and interactions. By combining these techniques with traditional machine learning approaches, the model can deliver highly tailored and engaging experiences. This research contributes to the advancement of personalized customer experiences, empowering businesses to build stronger customer relationships and drive business growth.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/icacrs62842.2024.10841633
Citations
4
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.11
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article

Artificial Intelligence in Product Management: Enhancing User Experience Personalization through GenAI

Pankaj Pilaniwala
4 citations
Big Data and Business Intelligence
2.11
article

Artificial Intelligence in Product Management: Enhancing User Experience Personalization through GenAI

Pankaj Pilaniwala
article en
4 citations

Abstract

In today’s digital age, personalized customer experiences are crucial for businesses to thrive. Traditional methods of customer experience personalization often rely on static models that struggle to adapt to dynamic consumer behaviors and preferences. This research study proposes a novel dynamic integrated model that leverages Generative AI to continuously update and refine customer experiences. By analyzing multi-dimensional data sources such as transaction history, online interactions, and social media activity, the model can capture the evolving nature of customer preferences. This research study explores the potential of integrating advanced algorithms like Generative Adversarial Networks (GANs) and Large Language Models (LLMs) to generate personalized content, recommendations, and interactions. By combining these techniques with traditional machine learning approaches, the model can deliver highly tailored and engaging experiences. This research contributes to the advancement of personalized customer experiences, empowering businesses to build stronger customer relationships and drive business growth.

University of Arizona (US)
Decent work and economic growth
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.11
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