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 AI powers Adobe Commerce Product Recommendations, 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.

NOTE
If your storefront is implemented using PWA Studio, refer to the PWA documentation. Learn how to integrate Product Recommendations in a headless environment if you use a custom frontend technology such as React or Vue JS. 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 AI intelligence services are leveraged on the SaaS side.

Product recommendations architecture diagram

Once installed and configured, the recommendation modules enable your storefront to collect behavioral data. Adobe AI combines this data with your catalog data to calculate product associations used by the Recommendations service. You can then create, manage, and deploy product recommendation units directly from the Admin UI.

Next steps

Read the following topics to get started with Product Recommendations:

recommendation-more-help
commerce-help-product-recommendations