Personalized recommendations play a crucial role in enhancing the online shopping experience. They help customers discover relevant products, increase average order value, improve customer retention, and boost conversion rates. Two main types of recommendation engines are collaborative filtering (based on user behavior) and content-based filtering (based on item features). Hybrid models that combine both approaches can provide more accurate recommendations. Algolia's ecommerce recommendation system uses a hybrid engine to deliver high-quality suggestions, improving customer engagement and driving business growth.