Personalization Glossary

At PSYKHE, we're obsessed with the why: Why do we like the things we like? Why does one person like a pair of shoes, a sofa, a travel destination, or a song, while someone else does not? Understanding all the factors that drive individual taste, including personality and psychographic data, enables us to create the world's most sophisticated recommendation engine. After all, you can't personalize without personality. Shaping a stellar recommendation strategy is a big job, so to help you grasp what a complete AI personalization blueprint for your business entails, we've collated definitions related to personalization here.

Content-Based Filtering

The content-based filtering method uses intrinsic information about items and users to understand what features of an item a user might like. In contrast to collaborative filtering, content-based filtering does not require other users’ data to provide personalized recommendations to a user. This flexibility allows the system to provide highly specific recommendations to the current user, but it is also limited in the sense that it is unable to expand on known user interests.