AI-Driven Personalization in Digital Marketing a New Model for Predicting Consumer Behaviour

Artificial Intelligence (AI) has turned into one of the most profound digital marketing disruptors that allowed companies to provide highly personalized and data-informed consumer experiences. Conventional marketing strategies that are mainly rooted on the demographic segmentation framework are becoming insufficient in order to capture the complexity of the new consumer behavior. But the opposite, AI-based personalization relies on machine learning algorithms, predictive analytics, and real-time data processing to know and predict individual consumer preferences (Davenport et al., 2020; Huang and Rust, 2021). The proposed study is aimed at developing a new conceptual framework that combines AI technologies, behavioral, and psychological elements to become a better predictor of consumer behavior. The model is a strong framework of enhancing engagement with customers, their intention to purchase a product and their brand loyalty by integrating the data collection system, intelligent processing engines and adaptive personalization engines. The study will use a systematic literature review method in establishing major variables and associations between AI and personalization in digital marketing (Wedel and Kannan, 2016). The results indicate that AI-based personalization is extremely effective in marketing by providing a platform to respond to customer needs and points in real-time and dynamically. Nevertheless, the data privacy issues, ethical issues, and algorithmic bias also present a challenge that is of utmost importance (Martin and Murphy, 2017). The study can fill the gap in the literature, as it can help fill a gap between predictive analytics and consumer psychology, including theoretical considerations and practical implications as a marketer and researcher.