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Recommendations AI enables you to build high quality personalized product recommendation systems without requiring a high level of expertise in machine learning, systems design, or operations. Leveraging your website’s catalog products and user behavior, Recommendations AI builds a recommendation model specific to your company, including optional add-on features such as result diversity, selecting whether you are optimizing for CTR/CVR/Revenue, and shopping feed integration (all available by request to the support team). You can then request recommendations for other catalog products to display to your users.
In order to build recommendation machine learning models, Recommendations AI needs two sets of information:
- Product catalog: Information of the products sold to customers. This includes the product title, description, in stock availability, pricing, and so on.
- User events: End user behavior on your website. This includes users searching for, viewing, or purchasing a specific item, your website showing users a list of products, and so on.