Using traditional music research and chart monitoring is “backcasting”. Using MUSICDATAK is “forecasting”.

Create playlists that captivate your audiences' attention now.

Our clients

Armed with specific knowledge about which songs are now most loved, shared & added to playlists, broadcasters can plan out better music programming and scheduling strategies.

They also have an edge over competitors who don’t have access to such data.

Our happy clients.

Jérôme Delaveau 
Radio Star General Manager   

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.   

Bruno Witek
Consultant Programmer MISTRAL FM and Founder of Fanscore Music

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.

Christophe Mercier
Director of Oxygène and Vosges FM 

We are ultra local, and with MUSICDATAK we scan the ultra local digital market. Our music is now more targeted to our regions.

Musicdatak has a data-based approach that allows radio stations to enhance their playlists for a more vibrant listening experience that gets listeners to stay longer. 

Musicdatak offers radio stations better insight into their listeners by capturing a more detailed level of information about their actual preferences on music streaming platforms and social media. 

Meet our team.

Samuel Zniber
MUSICDATAK Founder & CEO

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
Director of Operations.

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
ENGINEER SPECIALIZED IN DATA SCIENCE - MACHINE LEARNING

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).

As part of our radio playlist decision optimization process, our AI provide recommendations based on your current strategy.

You will be enhancing your current programming decisions making your programming more effective.

ZN1BER MED1A LAUNCHES  MUSICDATAK.

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.

ZNIBERMEDIA LAUNCHES MUSICDATAK A MUSIC SEARCH ALGORITHM. 

MusicDatak automatically calculates many relevant data sources from music platforms, radio stations and music rankings on social networks. 

AUDIO : LAUNCH OF MUSICDATAK TO DETECT THE BEST MUSIC HITS.

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.

It’s often too easy to make assumptions about what will keep listeners tuning in. But true success comes from understanding your audience’s desires on a deeper level.

The radio business has changed so much over the past several years with digital radio, streaming services like Pandora and Spotify, as well as online options such as iHeartMedia and TuneIn Radio.

Understanding how often certain songs are played relative to others in the market is crucial in constructing playlists that appeal to your target audience.