Prior to the internet, there were plenty of numbers for measuring a musician’s audience: fan clubs, concert sizes, mailing lists, etc. What Baym points out is that all of these were ways of measuring audience but the primary purpose was communication, not data research. There would certainly be overlap but the need for a mailing list is to tell fans about a musician, where following an artist on YouTube in a way performs that information backward. Where that fan is represented as a single addition to a visible number of subscribers, rather than first existing as someone ready to receive mail for fans.
It’s a small but crucial point to remember because the visibility of such stats on the digital platform warps the perspective that people hold vast audiences at their fingertips. Reality would show only a fraction of consumers is ready to receive that information, unlike those who buy a concert ticket, which does show a rather deeper commitment to an artist beyond pressing a single digital button.
This issue of fully comprehending how to use such information ends up becoming a rather explicit labor issue for musicians. Baym writes:
However magnificent it may seem to have so much data available and to be able to mobilize that material in different ways, the promises of big data are a mixture of real potential with uncritical faith in numbers and hype about what those numbers can explain (Boyd and Crawford, 2012; Bruns, this issue). To even begin to make sense of the data, people need expertise and skill as well as software and human resources.
This analysis runs counter to the way Apple Music or Spotify for Artists are often portrayed. The accepted norm is to give raw data to a musician and leave it up to them to capitalize on it. Baym’s interviews with musicians complicate that messaging since musicians are not trained data scientists, so accumulating more numbers just adds a new skill for these workers to have to learn. This is a trend that’s become more normalized throughout the decade, so when Daniel Ek delivers quotes
like “We’ve never before been at a place in time where you could make as many informed decisions and understand your audience as well as we can do now as an artist,” it masks the fact that more weight is put onto musicians and their teams. Many artists can, and do, adapt to this new system or have people within their team to do it, but no amount of three-minute videos can help with what is effectively a new digital-first job created.
This lack of complete understanding, especially with new metrics being spawned every few months, makes it seem like the industry is always chasing a new arbitrary number. Spotify talks about its bullshit Monthly Listeners stat
, Apple loves the equally horseshit pre-saves
, and YouTube constantly talks about bulk quantity views, which are known at this point to be easily fabricated
. The assumption that musicians must
use their data and information creates a troubling feedback loop where these metrics that are mostly created for advertising, not really for measuring fan engagement, are how artists are told to measure their career trajectory. Thus, if an artist doesn’t have enough monthly listeners, it can look bad. When in reality, as Baym’s essay notes, that platform may not be where the artist’s audience is found.