Product recommendations typically use data analytics and machine learning algorithms to analyze customer behavior. Here are some common methods:
Collaborative Filtering: This method makes recommendations based on the preferences of similar users. Content-Based Filtering: This approach recommends products based on the features of the items that the customer has liked in the past. Hybrid Methods: Combining multiple algorithms to improve the accuracy of recommendations.