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Can we forecast trends and popularity in music?

Can we predict how a new release will be received in social media and on streaming services?

Can we predict how many tickets that will be sold for a concert or a festival?

Can we predict genre trends for different markets?

Can A&R´s use predictive analytics based on machine learning to detect early trends and get insights for the future?

There are the questions that our FuturePulse team, Saki Markovic from Playground Music Scandinavia, Gonçal Calvo from BMAT and Daniel Johansson from Soundtrack Your Brand will answer, during our Breakout Session on Thursday October 22nd, at 16:30 - 17:15, during the c/o pop Convention 2020 - xoxo Edition

During our project’s Breakout Session, you will learn amongst others how FuturePulse:

  •   Predicts genre popularity trends on different markets based on Spotify Top 200 charts.
  •   Combines open and confidential data (from labels/distributors/radio) into combined timelines, with up to 12 week predictions of what will happen on platforms like Spotify, Apple Music, Deezer, SoundCloud, Facebook, Twitter, YouTube, radio channels globally etc.
  •   Uses advanced Audio Descriptors for music, that identifies such things as moods, situations that are used to predict which songs are the best in playlists,
  •   Automises genre classification based on audio analysis (without the need to tag music manually).
  •   Predicts which playlists that will give the best results for a certain track (based on audio profiling and historic results from similar tracks and artists by maching learning).

You will also get to know:

  •   The model Venue Rank predicts which live venues are the best for certain artists when it comes to social media engagement.
  •   The model T-REC predicts recognition levels of songs, not only popularity, but also how well recognised a song is on a certain market.

The Breakout Sessions will be presented by FuturePulse and We Are Europe and will be accessible only by registration

Click here to get your free Online Ticket!

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Co-funded by the European Commission

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 761634. This website reflects the views only of the Consortium, and the Commission cannot be held responsible for any use which may be made of the information contained herein.