What is collaborative filtering?

Collaborative filtering recommends items based on what similar people liked or bought. It is the logic behind “customers who bought this also bought.”

Collaborative filtering looks for patterns across many customers. If people who bought one product also tend to buy another, a new customer who buys the first is shown the second. It needs no understanding of the products themselves, only behavior.

Its weak spots are new or rarely bought items with little history, and content generated for a single person, which has no crowd behind it at all. That is why most systems combine it with content-based methods that use product attributes, descriptions and images.