Product Recommendations Administrator Development

Product Recommendations are a powerful marketing tool you can use to increase conversions, boost revenue, and stimulate shopper engagement. Product Recommendations are surfaced on the storefront in the form of units such as “Customers who viewed this product also viewed”, “Customers who bought this product also bought”, “Recommended for you”, and so on. Adobe Commerce Product Recommendations are powered by Adobe Sensei, which uses artificial intelligence and machine-learning algorithms to perform a deep analysis of aggregated shopper data. This data, when combined with your Commerce catalog, results in highly engaging, relevant, and personalized experiences for the shopper.

If your storefront is implemented using PWA Studio, refer to the PWA documentation. If you use a custom frontend technology such as React or Vue JS, refer to the user guide to learn how to integrate Product Recommendations in a headless environment. Headless instances must implement eventing to power the Product Recommendation workspace.

Architectural overview

At a high level, Commerce Product Recommendations are deployed as SaaS. The Commerce side includes the storefront, which contains the event collector and recommendations layout template, and the backend, which includes the Data Services, SaaS Export module, and the Admin UI. Adobe Sensei intelligence services are leveraged on the SaaS side.

Product recommendations architecture diagram

Once the recommendation modules are installed and configured, your storefront will begin collecting behavioral data. Adobe Sensei processes this behavioral data along with your catalog data and calculates product associations that are leveraged by the recommendations service. At this point, the merchant can create, manage, and deploy product recommendation units to their storefront directly from the Admin UI.

Types of data

Product Recommendations require the following data:

  • Behavioral - Data from a shopper’s engagement on your site, such as product views, items added to a cart, and purchases. Commerce and Adobe Sensei do not collect personally identifiable information.

  • Catalog - Product metadata, such as name, price, availability, and so on.

When you install the magento/product-recommendations module, Adobe Sensei aggregates the behavioral and catalog data, creating Product Recommendations for each recommendation type. The Product Recommendations service then deploys those recommendations to your storefront.

For configurable products, Product Recommendations uses the image of the parent product in the recommendation unit. If the configurable product does not have an image specified, the recommendation unit will be empty for that specific product.

Next steps

Read the following topics to get started with Product Recommendations: