This paper explores the role of recommender systems in enhancing e-commerce, particularly in increasing sales, cross-selling, and customer loyalty. It provides a comprehensive overview of how these systems work, their applications, and their impact on e-commerce businesses. The authors analyze six e-commerce sites that use recommender systems, including Amazon.com, CDNOW, eBay, Levi's, Moviefinder.com, and Reel.com, to understand their implementation and effectiveness. The paper also presents a taxonomy of recommender systems, categorizing them based on the degree of automation and persistence, and discusses various user inputs and methods for finding recommendations. Finally, it outlines future opportunities and challenges in the development and application of recommender systems, emphasizing the importance of balancing customer value and business goals.This paper explores the role of recommender systems in enhancing e-commerce, particularly in increasing sales, cross-selling, and customer loyalty. It provides a comprehensive overview of how these systems work, their applications, and their impact on e-commerce businesses. The authors analyze six e-commerce sites that use recommender systems, including Amazon.com, CDNOW, eBay, Levi's, Moviefinder.com, and Reel.com, to understand their implementation and effectiveness. The paper also presents a taxonomy of recommender systems, categorizing them based on the degree of automation and persistence, and discusses various user inputs and methods for finding recommendations. Finally, it outlines future opportunities and challenges in the development and application of recommender systems, emphasizing the importance of balancing customer value and business goals.