Summary
By using product recommendations, retailers offer their customers the ability to discover new, relevant products that they might potentially want and learn more about. When recommendations are used to enhance product discovery, they create more conversion opportunities, help increase sales revenue, and amplify customer satisfaction and retention.
The available types of automated product recommendations in Commerce use AI and machine learning to produce contextually relevant product suggestions for customers based on purchase behavior and trends. Retailers have the option of adding multiple list types, including curated, algorithmic, contextual, and personalized recommendations. The recommendations service is an omnichannel tool that helps empower retailers with new opportunities to interact with their customers throughout their product discovery journey.