Delivering Dynamic, Personalized Experiences with Adobe Target’s New User-Based Recommendations Algorithm

Your customers have more choices available to them than they’ve ever had before. Their expectations for a personalized experience are set high by personalized experiences delivered by companies like Netflix, YouTube, Spotify and Amazon. As a marketer trying to create engaging digital experiences, you need to personalize your customers’ interactions with the most relevant products, content or services, and dynamically update those offerings in real-time as users move through their journeys.

Adobe Target Recommendations’ new User-Based Recommendations algorithm allows you to deliver an individually personalized “Recommended For You” experience to each of your customers that is tailored to their unique behavior. These recommendations go beyond single-key approaches such as “favorite category”, “last viewed brand” or “people who viewed this, also viewed”, and instead use the totality of a customer’s behavior to infer their underlying preferences. For example, a user browsing a purple scarf in the winter may receive a recommendation for gloves in a complementary color; when the user returns in the spring and browses running shoes, recommendations update in-session to reflect the new interest, displaying a tank top – but may retain knowledge of the user’s preference for purple.

Our new algorithm is powered by Adobe Sensei and builds upon machine learning models developed by Adobe Research to power recommendations on Behance, Adobe’s discovery platform for creative work. Our approach differs from previous options by:

The result of our Data Science and Engineering teams’ work is an algorithm that analyzes billions of customer interactions with millions of pieces of content to create personalized recommendations for your customers, no matter what your business is.

Getting started is easy for Adobe Target Premium customers who have implemented Target Recommendations. Just add the Recommended For You criteria to one of your pages:

Or create a new Criteria and select the User-Based Recommendations option for your Recommendation Logic after selecting any item-based Recommendations Key choice (Last Viewed Item, Last Purchased Item, Current Item, or Most Viewed Item):

The selected Key doesn’t drive the User-Based Recommendations algorithm, but allows you to use Adobe Target Recommendations’ filtering options, so you can apply business logic and context to ensure a great customer experience.

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