Which Approach to Recommendation Engines is Right For Your Organization?

A collaborative filtering model leverages similarity between your users to make suggestions rather than focusing on concrete details about a particular item. Typically these systems use rating or purchase history to compare users to each other. The distance between pairs of users is calculated, and a particular user is matched to others that are "close" to him or her (i.e. have similar tastes). For a clothing company employing this model, a user would be shown a Balmain jacket if their transaction history was similar to another user who went on to purchase that jacket. In contrast, with a content-based system, that recommendation would have been made based solely on that user's history, without considering the behavior of others.