Harnessing Artificial Intelligence for Hyper-Personalization in Digital Marketing: A Comparative Analysis of Predictive Models and Consumer Behavior

Abstract

In this research, the impact of AI in improving the extent of hyper-personalization in digital marketing is explored by comparing and contrasting the outcomes of the various predictive models with consumers' behavior. With the change in customer demands, companies are now incorporating AI technologies in the production of services and products that cater to the customer's needs. Thus, the study uses quantitative and qualitative interviews to examine the extent to which the different types of predictive models can contribute to hyper-personalization initiatives. Studies show that organizations that have adopted hyper-personalization through AI reap significant benefits in terms of customer interaction, satisfaction, retention, and higher conversion rates arising from segmented marketing. However, data privacy issues and issues related to the ethical use of the data are also pointed out, which have to do with data responsibility. As such, the study establishes that applying best practices and developing superior and sophisticated forms of AI enables organizations to build valuable and relevant customer experiences that lead to organizational success in the current environment.