Automated Personalization
Automated Personalization (AP) uses advanced machine learning algorithms to deliver personalized experiences and improve conversion rates for digital interactions.
AP records visitor activity, building profiles to target content to similar visitors. AP tracks responses to content for individuals and the population, using sophisticated modeling to automatically target each visitor based on everything known about them.
AP is fully automated, continuously learning with minimal human analysis. It builds models to determine which products a visitor is likely to be interested in, collecting and storing information in visitor profiles. Multiple algorithms ensure the best model for your system.
Auto-Target
Auto-Target uses advanced machine learning to identify high-performing marketer-defined experiences. It then delivers the most tailored experience to each visitor based on individual customer profiles and the behavior of previous visitors with similar profiles. Auto-Target helps personalize content and drive conversions.
Recommendations
Recommendations activities automatically display products or content that might interest your customers based on previous user activity. Recommendations help direct customers to relevant items they might otherwise not know about.
A recommendation determines how a product is suggested to a customer, depending on that customer’s activities on the site. For example:
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Encourage people who purchase a backpack to consider buying hiking shoes and trekking poles.
Create a recommendation that shows items that are often purchased together, using the “People who bought this also bought that” criteria.
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Increase the time visitors spend on your media site by recommending similar video content to what they are currently watching.
Create a recommendation that suggests other videos, using the “People who viewed this viewed that” criteria.
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Suggest that customers who viewed information about savings plans at your bank also read about IRA accounts.
Show other products people purchased after viewing one product without showing the first product in the recommendations, using the “people who viewed this also bought” criteria.
Recommendations as an offer
Recommendations as an offer lets you include recommendations inside A/B Test, Auto-Allocate, Auto-Target, and Experience Targeting (XT) activities.
This functionality opens up entirely new capabilities, such as:
- Test and target recommendations and non-recommendations content within the same activity.
- Easily experiment with placement of recommendations on the page, including the order of multiple recommendations.
- Automatically push traffic to the best-performing recommendations experience using Auto-Allocate.
- Dynamically assign visitors to tailored recommendations experiences based on individual profiles using Auto-Target.
Enterprise User Permissions
Enterprise User Permissions functionality lets you create different projects (called “Product Profiles” in the Adobe Admin Console for Enterprise). Enterprise User Permissions let you assign different permissions for a single user that dictate that user’s access rights for each project. These distinct projects can be compared to the way that report suites work in Adobe Analytics. Each project can have specific users with specific roles that apply to a set of properties. The result is that customers are able to restrict the view, edit, approval, and publish access to their users. You can restrict users based on region, environment (dev/stage/prod), channel, or other custom criteria.
