Item segmentation is an abstraction on top of the catalog of items that allows you to group items into segments based on their properties which can be then recommended to your users.
Audiomack was our very first customer who had a chance to properly test this revolutionary feature and measured exciting performance uplift in the artist following.
There were two use cases in the app to start with: recommending artists based on your music taste and similar artists based on the ones you are already following.
Rolling out this functionality was a huge success and helped increase registered users’ engagement and satisfaction with the platform.
Not only did it account for 10% of the total “follows”, but if a user clicks follow, there is a 9% chance they immediately follow another artist. If they follow one of the recommendations, there's a 75% chance they follow at least one more.