They also have an edge over competitors who don’t have access to such data.
A real opening on the outside by sweeping all the sources of musical discoveries. The personalization is total. You can segment by age group, favorite music genres, favorite radio stations, etc.
MUSICDATAK allows us to reach a digital audience. We broadcast Begging by Maneskin with MUSICDATAK recommendations. It's now a worldwide hit that is number 1 on Fanscore call-outs. We can create a cluster of positive differentiation.
We are ultra local, and with MUSICDATAK we scan the ultra local digital market. Our music is now more targeted to our regions.
Program director (Fun Radio, RTL2. RFM, Virgin Radio in France, The Beat 92.5 Montreal, Mix 106.5 Sydney, Magic 102.7 Miami, Galaxy 102 in Manchester) this radio maker has been developing the MUSICDATAK algorithm since 2019.
Marino Hernandez is the musical director and founder of Latin radio CHR Sonido 104 in the Dominican Republic. Based in France with a master's degree in Digital Business Analytics from Léonard de Vinci School of Management. Marino is currently developing MUSICDATAK.
Robin Lietar is an engineer from Mines de Paris, with a Master's degree in Data Science. Missions at the CSIRO research center in Australia (CNRS equivalent) in Twitter data extraction and categorization of tweets using NLP. Prediction of music listening on Deezer from a database of 8M entries (GPU based algos).
MusicDatak integrates a station’s 40 most-played songs each week. The system automatically assigns a “MusicDatak Satisfaction Score” to each, and makes weekly song recommendations for playlists.
MusicDatak automatically calculates many relevant data sources from music platforms, radio stations and music rankings on social networks.
MusicDatak is an automated process that detects hits, verifies information, organizes and prioritizes hits based on the level of satisfaction or fatigue of a specific audience at a specific location. MusicDatak targets radio stations, retail brands and music curators.