Product recommendations work through a combination of data collection, analysis, and machine learning algorithms. Here's a simplified process: 1. Data Collection: Gathering customer data such as browsing history, purchase history, and demographic information. 2. Data Analysis: Analyzing the collected data to identify patterns and preferences. 3. Algorithm Application: Using machine learning algorithms to predict which products the customer is most likely to be interested in. 4. Email Integration: Incorporating these recommendations into email content to create a personalized experience.