Students Partner with Industry Giants to Analyze Music Data in Real Time

An infographic created by Jorge Riveros M.A. ’20 featuring radio data for the Colombian hip-hop act Los Petit Fellas.

Music industry professionals need to stay up-to-date on the latest consumer trends and to accurately interpret data in order to make smart decisions about how to spread their art around the world. Students in the class Data Analytics in the Music Industry are learning how to help them do just that. 

In the course, which is part of the Master of Arts in Global Entertainment and Music Business program, students are challenged to use both logic and instinct—their brains and their guts—melding their musical knowledge with statistical and data-visualization skills. 

This spring, they had the opportunity to sharpen their skills by collaborating with major industry players. The class analyzed ticketing data under the supervision of Marisa Márquez, director of marketing for Live Nation Spain; built an algorithm to track KPIs for European artists with Anna Daus, head of business intelligence for Sony Music Germany; proposed a marketing campaign to singer-songwriter Kelli Leigh, working with Gareth Mellor, marketing director for AWAL/Kobalt; and forecasted emerging trends for ProSiebenSat.1 Media, under the guidance of data strategist Stefanie John, tackling social media data on podcasting, content individualization, and augmented reality (AR) applications. 

In each of these projects, students came up with fresh ideas that an executive or industry veteran, due to a lack of experience with next-generation tools such as TikTok, might not be able to envision. In turn, the professionals mentoring the students shared their knowledge of what is and is not possible. 

Analyzing artist performances requires access to primary data from music streaming services such as Spotify and Apple Music and social media companies like Facebook and Instagram. While each platform has its own process for bringing users into its ecosystem, some bridges exist between the platforms. 

In one assignment, students analyzed the global popularity of Lil Nas X’s TikTok-sensation-turned-smash-hit “Old Town Road,” using data provided by WARM (World Airplay Radio Monitor), to determine whether streams correlate with airplays. In another task, students were asked to select a song, build a research question to collect metadata and streaming data, then write the story of the life of the song based on how long, in what territories, and on which media, it’s been played. They also accessed primary data from Spotify for Artists and Facebook Business Manager for acts such as Monarchy, working with the band’s manager, Cindy Castillo.

It was crucial for students to compare the pros and cons of each data analytics platform available on the market. Over the course of the semester, students deepened their knowledge of Chartmetric (thanks to founder/CEO Sung Cho), Soundcharts (thanks to founder/CEO David Weiszfeld), WARM (thanks to founder Jesper Skibsby), Pollstar Pro, BuzzAngle Pro, and Next Big Sound. 

The main lesson students learned is that the perfect platform does not exist. While each service offers its own advantages, the music industry remains fragmented in terms of metadata (publishing versus recording), territory (North America is data-abundant whereas Asia is data-scarce) and the overall quality of the data rendering services (mostly airplay-focused versus mostly streaming-focused).

Given the diverse datasets the class has to study in the music industry, learning the data-curation process is key to delivering an accurate analysis. In addition to learning complex functions in Excel and Google Sheets, students honed their skills in Tableau Desktop, which they used to build an infographic painting a clear picture of the success of their favorite artist.

Students learned that advanced spreadsheet functions—such as vlookup, pivot tables, and slicers—can be tremendously helpful to analysts building comprehensive dashboards for musicians. Artist performance is multicriteria (e.g., streams, likes, airplays) and so is the analysis. The class explored the importance of building an index using weighted average and normalized data to reflect this performance. 

The need for data analysis and digitalization will only continue to accelerate. By working in collaboration with major music companies and gaining in-depth knowledge of the latest analytics platforms and data-curation tools, Berklee students have an edge in the increasingly competitive global job market. 


Alexandre Perrin is an associate professor at Berklee’s campus in Valencia, Spain, where he teaches Data Analytics in the Music Industry and courses on Entrepreneurship, Music Business Finance, and Global Leadership. 


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