AI-Driven Marketing Insights: Harnessing Machine Learning for Enhanced Consumer Engagement and Personalization

Businesses are depending more and more on AIdriven tactics to improve client engagement and customization in today’s cutthroat digital market. In particular, logistic regression is used for categorization and linear regression is used for predictive analytics in the its proposed AI-driven marketing strategy. Impressive results were obtained when the framework was tested using real-world data: $\mathbf{9 2 \%}$ accuracy in classification tasks, 94% accuracy in regression tests, and notable increases in customer engagement. Important data points include a 3.5% conversion rate, a 4.2% click-through rate, an average session duration of 5.1 minutes, and a 78% total engagement rate. These results show how the framework may lead to more successful customized marketing tactics. The study demonstrates that AI and ML improve consumer behavior prediction and personalized content delivery, which in turn boosts customer happiness and loyalty. Enhancing real-time flexibility and broadening the framework’s applicability across other marketing areas will be the key goals of future development.