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Quantitative Analysis of AI-Driven Predictive Analytics in Digital Marketing
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Author(s): P. S. Venkateswaran (Anna University, Chennai, India)and Nguyen Quynh Nhu Ngo (Ton Duc Thang University, Ho Chi Minh City, Vietnam)
Copyright: 2025
Pages: 32
Source title:
Strategic Blueprints for AI-Driven Marketing in the Digital Era
Source Author(s)/Editor(s): Rhytheema Dulloo (Hindustan Institute of Technology and Science, India), Anand Kurian (University of Exeter Business School, UK), Minja Bolesnikov (Swiss School of Business and Management, Switzerland), Ilse Struweg (University of Johannesburg, South Africa)and Kaliyan Mathiyazhagan (Thiagarajar School of Management, India)
DOI: 10.4018/979-8-3373-3897-2.ch007
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Abstract
This study examines AI-powered predictive analytics in digital marketing, analyzing customer behavior and personalization impacts. Through a quantitative analysis of 207 respondents, the research reveals a gap between AI tool adoption (30% regular usage) and their demonstrated effectiveness, with recommendation systems showing high consumer relevance despite low conversion rates. Statistical analysis demonstrates strong correlations between customer experience and digital shopping behavior, with interconnections between personalized content quality and prediction accuracy. The study identifies distinct clusters in user behavior patterns, highlighting the relationship between AI trust indicators and traditional shopping patterns. These findings provide valuable insights for organizations seeking to optimize their digital marketing strategies through AI implementation while addressing the current challenges in adoption and effectiveness.
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