Understanding Artist Growth Patterns With Predictive A&R: Part 1
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.
Historically, A&R has been a gut-based endeavor that’s rested on a single question: Does the artist have that ostensibly unquantifiable “it” factor? The problem today for gut-based A&R is the sheer volume of music that industry executives, aspiring scouts, and hit-making curators have to wade through to allow that experience-based gut power to function effectively.
To help reduce that volume, we followed the trajectories of a handful of artists that our Predictive A&R model first discovered in September in an effort to identify some early patterns of potential success by analyzing the relationship between Spotify Monthly Listeners (MLs), Spotify Followers, and Cross-Platform Performance (CPP).
As any good A&R team knows, scouting talent has never been about catching up; it’s always been about being there first. Today, that means identifying what early patterns in an artist’s streaming trajectory indicate the potential for sustained growth and a fruitful career, ideally at scale.
So, are there data trends and data relationships early in an artist’s career that might serve as correlates to — or at least supplementary information about — the “it” factor of traditional A&R? If so, is there an optimal route to follow, or are there many different roads leading to the same destination?
