<p>The rapid advancements in Artificial Intelligence (AI) and Machine Learning (ML) have transformed marketing into a data-driven approach, offering businesses unprecedented opportunities to optimise decision-making, enhance customer experiences, and achieve sustainable growth. However, the grocery retail sector faces unique challenges, such as balancing sales growth with customer loyalty, integrating complex datasets, ensuring predictive accuracy, and adhering to ethical data practices. This study fills these gaps by presenting the RAISE Framework (Robust Analytical Insights for Sales and Engagement), a thorough and scalable market analysis approach designed mainly for the grocery sector. Advanced statistical techniques ensured the framework’s robustness and reliability. The results underscore the framework’s dual emphasis on improving sales and growing customer loyalty as interconnected measures, with dynamic pricing, predictive analytics, and personalisation identified as essential catalysts. Through the practical application of the RAISE Framework, grocery merchants can execute ethical, scalable, and data-informed strategies to enhance pricing, inventory management, and personalised marketing initiatives, thereby enhancing customer engagement and trust. This study develops a novel framework for data-driven decision-making and connects theory and practice by offering a validated model that satisfies the particular requirements of the grocery sector. The findings confirm data-driven marketing as a necessary strategy for success in fast-changing and competitive environments.</p>