A recommendation system works in e-commerce by analyzing user behavior and preferences to suggest products that users are likely to find appealing. Utilizing algorithms such as collaborative filtering, content-based filtering, or a hybrid approach, these systems tailor suggestions based on past purchases, browsing history, and user ratings. By personalizing the shopping experience, recommendation systems enhance customer satisfaction and can significantly increase sales and conversion rates. They help businesses understand consumer trends and encourage upselling and cross-selling, contributing to overall revenue growth in the competitive e-commerce landscape.