Use cases with AI Item Recommendations

Several types of recommendation can be achieved with this engine , this includes: 

• AI Personalized - Using Transformer models to predict the best product for each person based on the history of interaction events. 
• Most recently engaged - which can be tied to any interaction event, (as long as that data is being tracked in Braze in reference to the catalog) including use cases such as: 
  • Recently Clicked 
  • Recently Viewed 
  • Recently Liked 
  • Recently Engaged 
  • Recently Purchased 
• Most Popular - Which includes most commonly engaged with - tied to any interaction event. This can include
  • Most Viewed 
  • Most Purchased