How A&Rs use data to identify high potential artists

Photo cover by: Kelly Sikkema
Written by: Julie Knibbe
Published Mar 23, 2021
5 min read
  • Camille Moussard
    Camille Moussard
    Global Head of Talent Scouts
  • Milena Taieb Octobre 2021
    Milena Taieb
    VP Trade Marketing

Big data technologies reshape how talent scouts work to find the next rising stars. Let’s dive into this virtuous partnership between human and technological skills.

The challenges of scouting artists among millions of creators

Music production and distribution have never been more accessible. Artists have home studios in which they can record and produce songs in a matter of days. They can distribute their music on streaming platforms in just a few clicks. About 12 million creators publish music worldwide. 

For A&R (Artists & Repertoire) departments responsible for scouting and signing new artists, the number of new artists to discover is tremendous. Centuries wouldn't be enough to listen to all of them. For each artist who catches their attention, they must evaluate the artist's ability to engage and retain audiences in the long run. 

What A&Rs look for in data analytics tools

Believe and TuneCore have a unique dataset to tap into to identify high potential artists, with distribution services tracking music consumption in more than 100 countries on more than 150 digital stores. TuneCore artists recently reached the record-breaking milestone of $2 billion collected revenue

To decide on whether or not they should sign someone, A&Rs have dozens of KPIs to look at: social media and digital streaming platforms analytics, chart placements, ticket sales, to name a few. The task can be overwhelming. Hopefully, data analytics tools are helping them filter out among millions of artists releasing music. 

We have internal tools that help us identify high potential artists. Given our focus on digital distribution, we pay a lot of attention to how artists perform on streaming platforms: how many streams and followers they have, from where their streams were initiated, and how productive they are. The latter is one of the most important criteria: digital audiences want fresh music released regularly. It’s better to release a song or an EP every two months than wait for two years to drop a full album.

Camille Moussard, Global Head of Talent Scouts at Believe

Streaming services are putting more emphasis on song releases than albums now. Editorial and algorithmic playlists are their primary music discovery vehicle. An artist usually only gets one song featured in a playlist at a time. When they evaluate an artist, A&Rs look at how often artists release music. If they see a pattern of them posting songs on a regular basis, it’s a good sign. It means that they understand how digital promotion works and that they know how to engage their audience in the long run.

Jaycee, a very prolific DIY Australian musician, is a good example of such productivity. He recently finished his world record-breaking project #OneSongOneDream where from July 1st 2019 to January 1st 2020 he released a new song and music video every week for six months straight. Such commitment and growth got him under the TuneCore radar, which now actively supports his career. His work and authenticity paid off as he became a rising TikTok star (now close to 750K followers). He quickly reached more than 1M views on his latest hit "Who Are You": "I need a beat where people can dance to it {...} And now I need your help to make it viral". 



I need your help ❤️ Link in bio 🎉 #WhoAreYou #Jaycee #Australia

♬ Who Are You - Jaycee


Apart from productivity, A&Rs also look at how engaged fans are. Contrary to absolute follower numbers, engagement metrics provide more insights regarding how fans behave. On streaming platforms, engaged fans follow the artist and add songs to their own collection to listen to them again. In terms of KPIs, that translates into user-driven streams (streams that were initiated from user libraries, user playlists, favorite albums or artists, or from direct search) as opposed to algorithmic or editorial driven streams. The more streams an artist gets are user-driven, the better.

Combining data analytics with local expertise

A&Rs have always relied on their understanding of the music market and their own experience in signing artists. A&R expertise lies in their knowledge of their local markets. Fan behavior is very different from one country to another. Camille Moussard, Global Head of Talent Scouts at Believe, explains that every A&R in her team focuses on one territory and a few genres.

"I'd rather sign 100 artists on 1 market than 1 artist on 100 markets."

Her team follows all the tastemakers very closely for their genre, whether they are social media influencers or influential playlists. A&Rs are experts for their local market, and they have eyes and ears everywhere. A new name that pops on a playlist or a Youtube channel immediately catches their attention.

We define specific goals for each local market. Each team member develops their expertise on their local genre. For example, in the UK, one team member is dedicated to hip-hop while the other focuses on pop and dance.

Camille Moussard, Global Head of Talent Scouts at Believe

Last year, that’s how Nakry, a French Hip-Hop artist, got noticed. He was featured in one of Spotify playlists, and the A&R in charge immediately reached out to him.

Big-data technologies help A&R departments access and process a lot more information than they could ever do alone. They use data as a tool to help them find the hidden gems among thousands of new music released, and get insights and historical data regarding their career. A&R is getting more data-driven than ever before. Artists that have successful data points around their music can quickly get noticed. Data analytics tools can detect anything on their radar, and it's up to A&Rs to bring their expertise in the mix to fine-tune these tools.

Artists that are signed today usually have proven their potential independently first. Artist services come into play later on to help them take their careers to the next level. This new model disrupts how labels used to work and emphasizes artists and their management, enabling them to remain independent.