Enhancing Consumer Purchase Intention in Pakistani Market: The Role of AI Personalization, Prediction Accuracy, and Real-Time Engagement - Ullah, Naqeeb; Gulzar, Muhammad Faisal; Arshad, Asghar Ali (2025)
This study investigates the impact of AI-driven marketing strategies, specifically AI personalization, prediction accuracy, and real-time engagement, on consumer purchase intention. By integrating these variables into a unified framework, the study provides a comprehensive understanding of how AI technologies influence consumer behavior. The research adopts a quantitative design, utilizing survey data from 350 respondents who actively engage with digital marketing platforms. Structural equation modeling was employed to test the hypotheses, revealing that all three variables significantly enhance purchase intention. Prediction accuracy emerged as the strongest predictor, followed by personalization and real-time engagement. Furthermore, consumer trust was found to moderate these relationships, amplifying the positive effects of AI strategies. This study contributes to existing literature by addressing gaps in the combined effects of AI-driven strategies and highlighting the critical role of trust. The findings offer actionable insights for policymakers and businesses seeking to optimize AI applications in marketing. Practical implications include the need for trust-building measures, consumer-centric personalization, and accuracy-focused AI systems. By addressing these aspects, businesses can enhance consumer engagement, drive purchase intention, and foster sustainable growth in digital markets.