Product recommendations, powered by Adobe Sensei
AI-fuelled recommendations based on shopper behaviour, popular trends, product similarity and more.
You might also like … more options, better engagement
Many shoppers are browsers. They know they want something, but they’re not sure just what. That’s where product recommendations come in. Recommending relevant products to your customers is like giving them a personal shopper — one who can help them to find that “it’s perfect” item. Recommendations are good for business too. Not only are your customers happier, they often end up spending more than they planned.
That’s why we built the Product Recommendations feature and powered it with Adobe Sensei. With Product Recommendations, AI automatically suggests relevant products based on your shopper’s behaviour as well as specific product features. It’s the easy way to increase the impact of your digital merchandising effort without the manual work needed to find meaningful product affinities and it’s exclusively for Adobe Commerce merchants.
Download the free extension at our marketplace today.
Let AI help you to customise your product recommendations
Harness the power of Adobe Sensei
Consumers spend 40% more time shopping when experiences are personalised. Our industry-leading AI fuels a collection of algorithms that automatically analyse shopper behaviour to give them that personalised experience. No page tagging or manual analysis required — ever.
Choose the recommendation type you need
Shoppers that engage with a product recommendation are 2x more likely to return. That is why we provide a set of recommendation types you can use across various shop front pages. Shopper-based, item-based, contextual popularity-based and more are all strengthened by the continuous analysis of shopper behaviour by Adobe Sensei.
Streamline workflows and metrics
Easily create new recommendations with the streamlined workflow. A seamless integration with Page Builder makes it effortless to drag & drop existing recommendations onto pages being authored within page builder.
Please make sure that the "dexter.base.react.umd" and "dexter.base.consonantcardcollection" clientlibs have been added to the template's Page Policy