Product recommendations are a powerful marketing tool that you can use to increase conversions, boost revenue, and stimulate shopper engagement. Adobe Commerce product recommendations are powered by Adobe Sensei, which uses artificial intelligence and machine-learning algorithms to perform a deep analysis of aggregated visitor data. This data, when combined with your Adobe Commerce catalog, results in a highly engaging, relevant, and personalized experience.
Product recommendations are surfaced on the storefront as units with labels, such as “Customers who viewed this product also viewed”. You can create, manage, and deploy recommendations across your store views directly from the Adobe Commerce Admin.
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, learn how to integrate Product Recommendations into your headless storefront.
There are many ways to develop a headless or custom implementation. This guide describes one way of doing so, using PWA Studio. It does not cover all scenarios or eventualities.
Given the ever-changing complexities of online shopping, what works best for your storefront is often a combination of multiple key technologies. Using both Product Recommendations and Product Relationships gives you more flexibility when promoting products. You can leverage Product Recommendations powered by Adobe Sensei to intelligently automate your recommendations at scale. Then, you can leverage Related Product Rules when you must manually intervene and ensure that a specific recommendation is being made to a target shopper segment, or when certain business goals must be met.
Product recommendations allow you to:
Watch this video to learn about Product Recommendations: