Published Paper Details:

In the rapidly evolving landscape of e-commerce and retail, the integration of predictive modelling, real-time data analytics, and artificial intelligence (AI) has significantly transformed pricing strategies, customer engagement, and operational efficiencies. This research investigates the implementation of predictive analytics techniques for new product pricing, the role of real-time data processing in enhancing business agility, and the transformative impact of AI in delivering personalized consumer experiences. Predictive modelling techniques leverage historical data, market trends, and consumer behavior to optimize pricing decisions, while real-time analytics architectures utilizing technologies like Apache Kafka and Apache Flink facilitate immediate insights into inventory management, customer preferences, and dynamic pricing.This paper presents a comprehensive analysis of how these technologies collectively empower businesses to achieve operational excellence, enhance customer satisfaction, and sustain competitiveness in the digital marketplace. Ethical considerations regarding data privacy and algorithmic fairness are also highlighted, ensuring responsible deployment of AI- drivennsolutions. The study ultimately emphasizes the critical role of data-driven, real-time, and AI- augmented approaches in shaping the future of e-commerce and retail industries.