Data-driven A&R: What is the future for the music industry?
In our day and age, data is one of the most valuable currencies in the world. The most prominent companies in the globe based their success upon knowing exactly what their clients do and like. The music industry started to follow the same approach, even if some branches arrived later than others. The main objective of this research is to understand how data analytics is used when scouting for potential talent, primarily by the A&Rs of record labels. Upon systematic research, I want to discover what tools are used to assess an artist’s performance and what implementations can be useful to consider. Those types of analyses are challenging because there are several aspects regarding artistry and the characteristics of a record that are difficult to gather through machine learning. Nevertheless, due to the impressive number of tracks that are uploaded every day on streaming platforms, reaching a certain degree of automation is mandatory. I interviewed different professionals from the Warner Music Group that are utilizing data A&R tools on an everyday basis, as well as consulting several papers and articles related to Music Information Retrieval (MIR) and predictive models.
Valencia (Spain) Campus
A&R; artist development; classification; data analysis; MIR; predictive models; talent scouting
Rocchi, Tommaso. “Data-driven A&R: What is the future for the music industry?.” Master's Project, Berklee College of Music, 2020. https://remix.berklee.edu/graduate-studies-global-entertainment-business/175