The use of recommendations has become essential for online buyers and media consumers, with nearly all user activity involving either search or recommendations. To deliver meaningful and relevant recommendations, developers need to build the data, algorithms, and user interfaces that capture user behavior, such as clicks, views, and conversions. The Algolia Recommend API allows developers to display and generate recommendations on various pages of their website, including product detail pages, checkout pages, category pages, and facets and categories. Recommendations can be generated using content-based filtering, collaborative filtering, or a hybrid approach that combines both models. Content-based filtering groups items based on similarity in attributes, while collaborative filtering generates item profiles based on user behavior. The Algolia Recommend API provides several features, including trends, frequently bought together, and anonymously captured user IDs to create item profiles. By leveraging these features, developers can optimize various stages of the customer journey and improve user engagement.