I use Algolia for used car dealership vehicle searching and filtering. I’d like to use the new Recommend product but cannot figure out if it works for this application.
Specifically, used vehicles are a small data set relative to the demo applications (20-60 vehicles in the data set at a time) and those products are constantly moving in and out of the set.
Obviously the vehicles share attributes that can/should power Recommend, like people who view trucks want to see more trucks.
Is Recommend appropriate for that kind of small, ephemeral dataset? Is it smart enough to abstract the common attributes and recommend based on that?