Use Profile Comparison to build Audiences in Adobe Target

The Profile Comparison feature in Adobe Target allows you to compare two numeric profile values against each other when building an audience. This is extremely helpful if you are, for example, passing custom-built propensity scores into Target and want to personalize content based on the product with the highest propensity score.


In this video, you learn how to:

  • Compare numeric profile values (scores) passed to Adobe Target
  • Use those score comparisons to define audiences

Intended Audience

  • Business Practitioner
I want to show you an audience building feature on target called Profile Attribute Comparison. This capability was built for customers who use offline data analysis to calculate propensity scores. Pretend you manage the website for this imaginary bank, We.Finance. You employ a data science team who aggregates data from web analytics, branch visits, call center activity and third parties. The team uses this data to build models, predicting the likelihood that a customer will sign up for a new account like a mortgage, a business credit card, an auto-loan or a premium checking account. A score is assigned for each product per customer. Now you’d like to personalize content based on these scores. So if a customer is interested in the mortgage you can remind them to fill out an application. You’re passing these propensity scores to target using profile parameters which you can confirm using the experienced cloud debugger. You could also pass them to target using our profile update API or the customer attributes feature of the people core service. To build your mortgage audience, use the options under Visitor Profile, first select the Propensity Mortgage attribute, next select the evaluator Is Greater Than and in the Comparison Type dropdown, choose Attribute. This will make a fourth dropdown appear in which you can select one of the other products, say Propensity Premium Checking. Add an “And” condition and repeat this for the other products. Making sure that the propensity for a mortgage is greater than the other scores. Now use this audience and then experience targeting activity to personalize mortgage content to visitors whose highest propensity is for mortgages. Now when you reload the page, you should see the Mortgage Message. You can build other audiences tied to the other products having the highest score and add them into your activity. Makes sense. Have fun and be nice to your data scientists. They don’t get out much. -

Additional Resources