The Role of AI in Shaping Content Marketing Trends Among Millennials: An Empirical Study

This paper aims to analyse the extent to which artificial intelligence has made its influence on the preference of content marketing among millennials. How predication analytics, automated content generation and AI driven personalization drive the customer engagement and purchase behaviour is what is studied. The research approach that was used was quantitative through survey of 196 millennial consumers. Convenience sampling was used because of the need to guarantee respondent accessibility. Confirmatory factor analysis (CFA), exploratory factor analysis (EFA), correlation analysis and ANOVA were used for confirming relationships between customer behaviour and use of AI in content marketing. Additionally, results from the study show that millennial engagement has a high positive association with AI — powered content marketing. Personalization and predictive analytics make sense in Customer satisfaction and it was found. In order to make amends, EFA and CFA were used to validate the structural model and confirm that AI was indeed the significant contributor in the improvement of content marketing efficiency.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/netcrypt65877.2025.11102439
Primary Topic
AI in Service Interactions
Type
article
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article

The Role of AI in Shaping Content Marketing Trends Among Millennials: An Empirical Study

M Janani, V. Andal
AI in Service Interactions
article

The Role of AI in Shaping Content Marketing Trends Among Millennials: An Empirical Study

M Janani, V. Andal
article en

Abstract

This paper aims to analyse the extent to which artificial intelligence has made its influence on the preference of content marketing among millennials. How predication analytics, automated content generation and AI driven personalization drive the customer engagement and purchase behaviour is what is studied. The research approach that was used was quantitative through survey of 196 millennial consumers. Convenience sampling was used because of the need to guarantee respondent accessibility. Confirmatory factor analysis (CFA), exploratory factor analysis (EFA), correlation analysis and ANOVA were used for confirming relationships between customer behaviour and use of AI in content marketing. Additionally, results from the study show that millennial engagement has a high positive association with AI — powered content marketing. Personalization and predictive analytics make sense in Customer satisfaction and it was found. In order to make amends, EFA and CFA were used to validate the structural model and confirm that AI was indeed the significant contributor in the improvement of content marketing efficiency.

Vels University (IN)
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AI in Service Interactions
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