Filter dynamically in Adobe Target Recommendations by comparing items (entities) against a value in the user’s profile.
Use Profile Attribute Matching when you want to show recommendations that match a value stored in the visitor’s profile, such as size or favorite brand.
The process for creating and using inclusion rules for criteria and promotions is similar, as are the use cases and examples.
The following scenarios show how you can use Profile Attribute Matching:
Profile Attribute Matching allows you to recommend only the items that match an attribute from the visitor’s profile, as in the examples below.
For example, you can use the Profile Attribute Matching option to create a rule that recommends items only where the brand equals the value or text stored in
profile.favoritebrand. With such a rule, if a visitor is looking at running shorts from a particular brand, only recommendations will display that match that user’s favorite brand (the value stored in
profile.favoritebrand in the visitor’s profile).
Profile Attribute Matching brand - equals - the value/text stored in - profile.favoritebrand
Suppose that you’re trying to match jobs to job seekers. You want to recommend only jobs that are in the same city as the job seeker.
You can use inclusion rules to match a job seeker’s location from his or her visitor’s profile to a job listing, as in the following example:
Profile Attribute Matching jobCity - equals - the value/text stored in - profile.usersCity
For a visual example of how profile attribute matching affects recommendations, consider a website that sells electric fans.
When a visitor clicks various images of fans on this website, each page sets the value of the
entity.size parameter based on whether the size of the fan in the image is small or large.
Assume you created a profile script to track and count the number of times the value of
entity.size is set to small vs. large.
If the visitor then returns to the Home Page, he or she will see filtered recommendations based on whether more small fans or large fans were clicked.
Recommendations based on viewing more small fans on the website:
Recommendations based on viewing more large fans on the website: