This is the second part of an essay on how artists and music professionals can best hone their digital and strategic literacy. You can read Part One of this essay, which was released on March 8, 2019, by clicking here.
To sum up the ideas from Part One: digital literacy is arguably a way of thinking first and a body of knowledge second, and the most effective educational tools for independent artists are modular and customizable, rather than prescriptive and one-size-fits-all.
Below are three additional threads on furthering digital and strategic literacy that I think could be helpful for music, inspired by my firsthand experience as a writer. Again, I’d love to hear your feedback on these ideas and whether or not you would agree with them—simply reply to this email and it’ll go straight to me!
2. Build an infrastructure that allows you to learn on a regular basis from outside industries.
The phrase “digital literacy” in and of itself is rather loaded, because the word “digital” touches nearly every company and job description today.
In fact, one could make the argument that almost every role at a modern music company is inherently a “digital” role, even if that word isn’t featured in the job description.
Hence I think one crucial component of digital literacy for any entrepreneur or businessperson is studying how the word “digital” impacts performance and decision-making beyond one’s immediate role and industry.
In the case of indie artists and their teams, that means establishing an infrastructure that allows for a consistent flow of information on how entrepreneurs in adjacent industries are approaching digital marketing, promotion and customer engagement.
Many musicians are already familiar with this approach on the creative side of their careers—e.g. developing an album or other project in collaboration with a carefully curated, like-minded group of artists coming from diverse backgrounds.
In fact, some of the most exciting music today is being created precisely from an unprecedented level of genre- and style-bending cross-pollination, facilitated in part by digital platforms lowering barriers to communication among otherwise disparate groups.
There’s no reason why this border-bending can’t apply to strategy—and building oneself a bespoke infrastructure for absorbing outside perspectives is more important than ever in the context of the online music business.
As long as artists are using the same platforms as other tech and media companies to market themselves—Facebook, Instagram, Snapchat, YouTube, email newsletters, etc.—they will face many overlapping problems, the solutions to which could provide a potent mutual learning opportunity. It’s no coincidence that there’s an increasing number
of people joining the music industry from the worlds of finance, tech and advertising to help build these solutions using outside expertise.
Given that many artists could also be considered CEOs of their own diversified companies
, they could also benefit from resources aimed at the wider SMB (small- and medium-sized business) community.
For instance, if you’re running your own direct-to-fan merchandise business as a musician, “merch literacy” arguably requires studying direct-to-consumer
retail startups (e.g. Away and Warby Parker), online DIY retail marketplaces and tools (e.g. Etsy and Shopify) and innovative, fan-centric merch companies across sports and other areas of entertainment (e.g. Fanatics
This approach has done wonders for me as a journalist. For instance, when it comes to inspiration for story ideas, I actually rely more on Medium posts from venture capitalists and tech founders than on the music-business trade press.
Getting into the mindset of VCs—whose job could be described as building a lucrative track record of looking around the corner and predicting disruptive shifts five years down the line, rather than simply thinking in immediate, short-term gains—has fundamentally shifted how I think about the future of music and media. Most importantly, it has helped me contextualize the music industry within a wider, complex ecosystem of forces in tech, finance and culture, and I believe my writing dramatically improved once I understood and actively incorporated this context into my pieces.
3. Learn to see through and critique data, instead of just blindly farming it.
In the spirit of point #2, I want to start off this section with an illustrative example from outside the music industry.
Last week, Digiday
reporter Kerry Flynn published a great article
about how advertisers interpret tech companies’ metrics on monthly/daily active users (MAUs/DAUs) with a grain of salt.
“Platforms always tell you the best possible number from the best possible angle, like people who only show you pictures of themselves from their good side,”
Duane Brown, founder of performance-marketing agency Take Some Risk
, said in the piece. “Counting those people who only login once a month for two minutes isn’t being genuine about who we can reach.” In other words, MAU/DAU numbers are irrelevant to advertisers’ specific demands for reaching more clearly-defined audiences.
I think the music industry can learn a lot from this mindset. For instance, at the outset of my talk on social media at the DIY Musician Conference last August, I asked the audience which platform out of Facebook, Instagram and Twitter they used the most often to market their music.
By far the most hands across demographics went up for Facebook—the reasoning being that Facebook had the largest user base, and therefore the widest possible reach.
While understandable, this response seemed to me like a desire to pursue quantity for quantity’s sake. Sure, Facebook might be the social platform with the largest scale, at 2.3 billion MAUs—but as Brown suggested in the Digiday piece, not even the biggest advertisers need or even want to reach that many people at once, because the quality of engagement will likely suffer.
A handful of artists are beginning to exercise similar scrutiny in how they allocate their marketing budgets. Electronic artist Example bought one of his fans a brand-new car
so that the latter could listen to the former’s new album Bangers & Ballads
, and Example has argued that the stunt was a cheaper yet more effective investment than spending money on boosted social posts.
“When I posted a photo of my fan with the car I bought him, 400,000 people saw that post,“ he said in an AWAL blog post
. "If I was going to do a promoted, boosted post to ensure 400,000 people saw it, it would have cost my $9,000, but I spent $3,000 on the car. You do the math.”
The need to gain more clarity and specificity around publicly-reported metrics is especially relevant to a trend I outlined in Part One of this essay—namely, that several of the major streaming services now offer and compete on some form of data transparency for artists, building dashboards of information such as geographic region and playlist attribution for streams around a given artist’s music.
To generalize to any digital context: Equally if not more important than the mere awareness of a technology, dollar amount or data source is the knowledge of what kinds of questions to ask about it.
Here also lies one of the pitfalls of the “content-marketing-as-education” approach from the streaming platforms themselves: they will likely not be the ones to encourage their artists/clients to scrutinize the statistics that they see.
4. Read up on mistakes, and be willing to share your own.
“We think of science as a hard and fast answer, when in fact it’s a process of uncertainty reduction.”
This is a quote from freelance science writer and editor Christie Aschwanden
’s interview on the Longform Podcast
that I think is so important for anyone in the music industry to think about.
Non-linearity is a feature, not a bug, in how the majority of artists and adjacent professionals build their careers today. Yet, human beings naturally perceive and want to pursue linearity. At its worst, this mindset leads to an over-reliance on pattern-matching, which then sinks into a false sense of reproducibility.
To unpack what this means, it’s helpful to zoom out and look at the growing concern in science at large about the lack of “reproducibility” of allegedly authoritative experiments.
In short, the reproducibility problem emerges when a seemingly robust study gets cited and endorsed thousands of times by other researchers—only to have the initial experiment itself revealed decades later as faulty and impossible to replicate, due to an abundance of confounding variables that weren’t originally accounted for.
As statistics and political science professor Andrew Gelman wrote
for the New York Times
, reproducibility issues often trace back to “researchers chasing patterns in noise
… all the careful procedure and all the honesty in the world won’t help if your signal (the pattern you’re looking for) is small, and the variation (all the confounders, the other things that might explain this pattern) is high.”
In this vein, reproducibility is a fruitless goal in music marketing. As many of you likely know already, it is virtually impossible to replicate the success of a given music-marketing campaign five years or even just days after the fact, since there are so many variables beyond the control of an artist or label that can affect a consumer’s ability or willingness to consume and enjoy a given piece of music, or to engage with a given social asset, at a specific time and place.
So how does one not fall into the mythical traps of linearity or reproducibility, but still stay sane and make smart, informed decisions?
One potential path is realizing that mistakes are much easier to replicate than successes, and such replication usually happens unintentionally.
To paraphrase a cliché, we don’t know the mistakes we don’t know—and if we don’t know them, we’ll just keep repeating them.
This is one of many areas where I think the music industry could potentially learn from the startup world.
During our Water & Music podcast interview
, Dan Runcie made a really compelling argument around the 14-minute mark that “UnitedMasters is, for all intents and purposes, an accelerator,” at least with respect to its promise to give independent artists the tools to build audiences on their own terms.
Another important element of the typical startup-accelerator environment that we didn’t cover in the podcast is the acceleration of feedback.
Consider Y Combinator, Techstars, 500 Startups and other global startup accelerators. Perhaps the biggest value proposition of joining one of these programs is the opportunity to access a sprawling network of alumni and mentors who can provide honest feedback on participants’ ideas and business models.
Importantly, these accelerators endure in popularity despite the startup success rate likely being even lower than that of the average indie artist: according to the U.S. Bureau of Labor Statistics, only three percent
of the country’s small businesses founded in 2011 lasted for five or more years.
In addition, just like music, tech entrepreneurship suffers from a lack of reliable reproducibility. The successful experience that a given mentor in an accelerator program had trying to build a startup in the early 2000s is nearly impossible to recreate today, as the modern social, cultural and technological climate introduces so many new confounding variables.
But even if there’s far from any proven formula for building a successful startup, that hasn’t stopped accelerators from facing ever-larger applicant pools of founders, or from continuing to offer a highly structured, bootcamp-style education for aspiring unicorn CEOs.
And studying past mistakes is a crucial part of any business education, startup or not. Zooming out from accelerators, if you read a typical Harvard Business School case study, the insights and discussions are as much about the pitfalls and bad decisions a company or CEO faced as about any positive or upward developments.
It’s debatable whether a fast-paced bootcamp/accelerator environment like Y Combinator would actually be helpful in the context of independent music. Nonetheless, what if there was a similar system for artist marketing that incorporated not only rapid-fire feedback from a carefully-selected network of mentors, but also an environment where mistakes—much more easily replicable than successes, to a fault—are explicitly acknowledged and studied in the open?
This is understandably difficult to do in an industry like music that’s so reliant on image and reputation. I’ve thought about this challenge especially in the context of conferences (I’m sitting on the floor of the Austin Convention Center as I type this, lol)—which are allegedly meant to serve as open forums for debate, but so often end up being surface-level performances instead, during which people are pressured to appear superior and authoritative rather than honest and open to change.
As conflict-resolution expert Priya Parker asks in her book The Art of Gathering
, which devotes many pages to suggestions for redesigning conferences: “Can we induce people trained to present themselves as perfectly baked loaves to bring dough worth sharing instead?”
The dough won’t always be pretty, but it will help people reduce their fear of failure and become more adaptable in the face of uncertainty. Again, we don’t know the mistakes we don’t know.