Josh is a data scientist at Chartmetric. He specializes in translating fuzzy, real-world interests into concrete, explicit questions to be directly connected to data structures and algorithms.
From Alt-Pop rappers to Indie-Folk singers, reaching a destination of digital success can involve many different routes. For A&R teams — and artists themselves — a comprehensive roadmap can be the difference between getting lost and getting discovered.
To vet how labels fared through the streaming transition, we tracked the trends of chart-topping tracks over the past 3-years and across 17 music markets. Below we discuss the most interesting, and most informative, results.
Chartmetric’s new A&R tools leverage machine learning to shortlist 1.7M musicians into the high-potential artists that interest you the most
How unsupervised machine learning and natural language processing (NLP) can identify artists’ genre neighbors
A detailed breakdown of how to instantly compare artists’ general performance by utilizing Chartmetric’s data warehouse
Breaking down men's & women’s performance on music charts
