
Spot trends ahead of time with pre-analyzed information.
Automatically identify underlying similarities that link communities together
Contact usClustering large catalogs offers many opportunities to enrich user pathways by finding similarities between items, identifying smooth user journeys or developing communities who would be interested in the same content.
Based on 15 years of analyzing user behaviors and performing constant metadata updates, our tools enable you to create relevant clusters in order to illuminate links between different items, categorizing them in fresh and intuitive ways.
Fast
Spot trends ahead of time with pre-analyzed information.
Scalable
Gather information from millions of data points.
Efficient
Automate analyses of millions of tracks and data opportunities.
At Deezer, we constantly organize and enrich our catalog based on metadata and user behavior analysis.
We build multidimensional clusters and link them to the right listeners, encouraging engagement through daily mixes and automated recommendations. We also use these insights to support our editorial team in their day-to-day job.
Build ready-made discovery channels and help your users to broaden their horizons through discovering similar artists/ albums/ songs to those they already like.
Propose a diverse audio experience that is based on end-user tastes, history, etc.
Offer your employees and partners new ways to use and understand your catalog, enabling them to work with clusters that, while initially hard to identify, are highly relevant.
Build audio journeys and take users from one mood/ song/ artist/ podcast to the next, using playlists that provide smooth transitions and make sense for them.
For instance, get curation insights to create the right journey for increasing dramatic tension in the soundtrack for a movie or TV show.
Reach new targets by offering audio that pleases your initial customer as well as the people around them.
Find music threads that are perfect for events or soundtracks for games and shows.
Spot artists that are often listened to in clusters, cross fertilize between fan bases and bridge communities. Enable your listeners to discover new artists and genres.
Identify hidden similarities and automatically highlight songs that would go well together in a DJ mix.
Would you like to know more?
Contact us