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:

  • 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.

  • 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.

  • 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.