Between 2020 and 2021, Music Tomorrow founder and Chief Executive Officer Julie Knibbe authored a comprehensive five-part series on music data for Water & Music, the preeminent music tech research community. Music Tomorrow is a knowledge hub for data-driven music professionals, and each edition from Knibbe covers a different industry vantage point, illustrating how music industry folk leverage data to do everything from structuring tours to marketing new releases to pitching artists. 

But beneath the metrics, Knibbe says, lies the imperative of storytelling. “The lower the barrier to entry in the music industry gets,” she wrote in the series’ first entry, “the more important storytelling becomes in rising above the subsequent noise.”

Since then, the barriers have continued to lower and that subsequent noise has become a shrill, omnipresent hum. There are 120,000 tracks uploaded to Spotify every day. Technology – via better DIY music-making tools, more direct distribution routes and now generative AI – continues to make it easier for anyone to make and distribute music.

For the music-loving hobbyists, that’s wonderful news, but when massive, one-size-fits-all streaming and social platforms – the places we consume content – fail to differentiate between hobbyists and professionals, the aspiring pros must put in ever more effort to garner attention, attract thousands of fans and, hopefully, eke out a living.

“Good numbers alone are not enough,” Knibbe wrote. “Cognitive psychology research has shown that a fact becomes 22 times more memorable when it is wrapped in a story. In order to build a compelling case around an artist, you can’t just have good music and promising business figures – you need a story to tie it all together.”

Emerging artists, then, have to deliver high-quality music content while amassing thousands of followers on major social platforms through high-quality, non-music content, and tie it all together with a cohesive, distinct narrative – probably while working at least one day job. The prevailing strategy? Build an audience you don’t own on social platforms that exploit your content for ad revenue, then painstakingly migrate those people elsewhere to consume paid-for music (at four one hundredths of a cent per stream). Welcome to the dismal state of platform capitalism. 

But even if one embraces the necessity of that heroic effort, how does one do it? If the community’s not gathering, is it the fault of the music? The story? The content strategy? Wrong tools? Not enough resources? It takes a lot of mental and emotional fortitude to steer the ship while reckoning with constant external feedback from all kinds of people: music folks and otherwise, assholes and otherwise. How does one tell what’s off the mark in order to make adjustments? 

Data, ostensibly, can be an objective bulwark to the emotional rollercoaster of sharing one’s art and story. Tracking and deriving insights from that data in resource-light ways that afford the time and space to keep creating art? That’s the hard part.

Throughout October, Water & Music and Music Tomorrow teamed up again to co-host their inaugural Music Marketing Data Bootcamp. Why now? The reason, they wrote, was simple: “Today, it’s hard to find a job in music that doesn’t involve working with data.” And that’s as true for artists as it is for music executives.

Over the month, a litany of industry leaders gathered to curate eight nutrient-dense sessions on music data, filled with case studies and actionable frameworks that might guide folks through the terrifying gauntlet of the digital marketing lifecycle. 

What persists, though, is the question of what should happen before there's data. “What data should a brand-new artist about to issue their first release, freshly launched new social, be looking to?” asked one of the bootcamp’s students in an early session. “Is it helpful to look at similar artists? Is there a way to test hypothetical campaigns? What advice do you have for a day-one scenario?”

The answers were expansive, with broad counsel that encouraged exploration, like “Test and learn,” and “Make your own data – keep track,” and “Don’t skip this step. Doing the groundwork pays off.” 

Day one scenarios are tough because, before the data, there’s just a story. And as Knibbe said during one session: “you have as many stories as you have artists.” 

Stories are singular. Data amasses and insights emerge at the unfurling of the story, which means that in order to truly understand the data, we need to observe it within the context of the story.

Like my day one scenario brethren, I’m one such artist trying to move from zero to something more than zero – overwhelmed enough by the gauntlet to be paralyzed at its start. So rather than simply recap the bootcamp and detail its contours – which I’ll also do – I’m going to heed the advice and apply it to my own nascent musical journey.

Across four pieces, I’ll reference the bootcamp’s valuable lessons and test them on the open waters that span web2 and web3. I’ll probably mess up a bunch but I’ll share that too, because mistakes are helpful, and sometimes even funny. As I move forward, the quirks and foibles will become part of my story, and hopefully they will help light the paths of other artists unsure how to take that first step. 

In this first round, I’ll be designing the lab, setting goals and preparing to get pummeled.

SESSIONS ONE AND TWO: Data practices + setting targets and benchmarks.

Folks from all over the world joined the bootcamp. Though largely concentrated in North America and the UK, the cohort had representatives from 20 countries, with people working across labels, startups, agencies and other functions that use data to support their work. 

About 60 people showed up to the first session, during which Knibbe summed up the reason we should all care about data: noise. Marketers have to be on their A-game, she explained, because there’s only going to be more music. The amount of people accessing data everyday continues to increase – to not use it is to disservice your story.

“Access to data is the throughline for this whole bootcamp,” said Maarten Walraven, co-project lead for the Water & Music Academy. “How do you get the data that you want? How do you visualize the data that you want from a dataset?”

Water & Music founder, Cherie Hu, added, “And then what do you do with that?”

Many of the first session’s open-ended inquiries began to gain shape in the second. What you can do with data is “set targets,” Walraven said. But because “there’s not a lot of literature on the methodology you can use,” the bootcamp attempts to elucidate where to focus and how to best take action.

Case studies help paint that picture. In one example, Christine Osazuwa, chief strategy officer at the ticketing platform Shoobs, shared a music campaign for a Swedish rock band that had an underperforming single. She was tasked with finding out why.

At the time Osazuwa was working at Universal Music Group. Major labels get access to all catalog consumption – anonymized data that shows the gender, geography, recent listening activity and age of streamers. 

Spotify also segments those listeners across active, previously active and programmed audience (i.e. passive listeners, “people that are listening on playlists”), so Osazuwa was able to segment the active fans – a largely 35-year-old male demographic – to see what else they were listening to. And the people who hadn’t listened to the single yet, she found, were listening to children's music (the joys of parenthood).

It’s one example on one platform for one use case in which data can clarify a pain point, but the overarching takeaway is: “audiences are living beings whose values and behaviors change.” 

Osazuwa explained that it’s important to cross-reference multiple streaming sources to understand who your people really are. Some platforms have different tools, like YouTube, which shows traffic sources to show how people got to your video. In aggregate, and with time, a picture emerges from the data.

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In her presentation, Knibbe dove deeper into the tools to explain how data indicates behavior. The percentage of your listeners in Spotify's active audience segment, for instance, is important, she said, because it signifies ongoing, intentional engagement.

There are also ways to tell if your tools are telling the story you set out to tell. “Look at your own artist or song radio,” Knibbe said, referring to the feature in Spotify that allows listeners to discover algorithmically similar artists or tracks, “and that will tell you how the algorithm sees you.” 

Maybe you don’t care how the algorithm sees you, but if your intention is to be a Dylan-esque bard and the algorithms have cornered you into the Christian rock section, listeners will think you’re a Christian rocker. Like it or not, algorithms dictate perception.

The same is true on socials, another layer in the vast plexus of digital storytelling. Vanity metrics – like number of followers – are one thing, but are people liking and commenting? Who are those people? What are they saying? And are any of them converting to deeper levels of engagement?

Knibbe calibrates these levels across a top-down funnel that moves through awareness, consideration, conversion, loyalty and advocacy. “How do you evaluate where you stand on each level of the funnel?” she mused. “You don’t want a leaky funnel.”

Indeed. And the answer, of course, is through data – by tracking it, understanding it and adapting as needed. But remember, emerging artists have day jobs, and they still have to make good music and share quality content. Tending to each part of the funnel is a huge amount of additional work.

“If you don’t have the resources to commit across the funnel,” Osazuwa asked Knibbe at the end of the second session, “what part of the funnel is most critical?”

“The middle,” Knibbe responded. “I don’t think you have to spend money to get to loyalty, and I would not spend money until I get loyalty.” 

“If I invest, I’d invest in nailing engagement, which is more about A/B testing,” she continued. “It’s that empirical phase of testing assumptions. I spend most of my time and money there, because once you have it, the top phase is the easy part.”

And how does one pursue loyalty? “Make your own data. Keep track,” Osazuwa said. “Don’t rely on third-party algorithms to dictate your careers. When there’s a new Tiktok or new Spotify, you’re gonna be in a whole world of trouble if you didn’t get people’s phone numbers or email addresses before that happened.

“Test and learn – every artist is very different,” she continued. “There are brand new artists that are slow burns and then there’s Ice Spice. There are a lot of different ways in which a new artist can exist. See what works and what doesn’t and keep track of that. You should probably look at how many fans you’re growing, what they like, are they engaging with you.”

“It starts with one,” Walraven added. “Get that one fan, make it two fans, four fans, eight fans…”

PARIAH CAREY

Ok, the table is set. We’ve got the info we need to get started. Before we make this actionable – which I’ll do more in the subsequent pieces – let’s summarize this wisdom: 

• Understand your story

• Set goals

• Choose the tools that help you tell that story

• Build a content strategy – across music and social – to achieve those goals

• Observe how people respond to your content 

• Track and adapt

I’ll be focusing on the first two bulleted points in this piece (the rest will come later in the series). 

Here are some additional insights gleaned from the session to help guide our path:

• Focus on getting one fan, not a million.

• Don’t adapt so much that you’re no longer telling your own story – be you.

• Use third-party algorithm data to understand how people are engaging with you, but make sure you own your community outside of those platforms. 

• Don’t spend money until you achieve loyalty.

Finally, Knibbe says to set “SMART” goals, which means: 

• Specific

• Measurable

• Achievable

• Relevant

• Time-bound

THE STORY

Life stories are beautifully long, but attention spans are not, so I need to choose which part of the story to focus on and how to tell it succinctly. And while data will inevitably play a role in how this story is told, all I have today is the narrative, so I’m orienting my story around a prompt of uniqueness: What is it about you that no one else has? What pieces of you make you a one-of-one?

With these questions in mind, I wrote my story here.

THE GOALS

First, why Pariah Carey? The wordplay, of course, and reference to one of the most successful artists of all-time. And fun fact: the word ‘pariah’ is actually derived from the Tamil word ‘parai,’ which means ‘a drum.’

But mostly, I’ve named this series Pariah Carey because while musicians you’ve never heard of aren’t pariahs, they may as well be. Algorithms treat them as such. Don’t want to play the game? Then don’t expect to get any attention. As Ben Folds said in clear, unfortunate truth:

“Self promotion. If you don’t want anything to do with it, stay in your fucking basement.”

I’m very early in my journey, with some fresh social accounts, a few live videos sprinkled about, no original music on Spotify or web3 platforms and a profound disdain for self-promotion. I’m trying to temper that discomfort with the hope that there are people out there who will find meaning in my music (and/or my story), and the mission to reach them is driving my own dive into music marketing.

To get there, I’m created some SMART goals that work toward my mission (which I’m tracking on a weekly basis here):

• Release my first song on Catalog and sell it to my first fan before the end of the year.

• Increase my Lens and Instagram followings by 100% by the end of January (this may seem aggressive, but my followings are very small right now)

• Release my second song and get 100 email addresses by the end of February.

• Find a music manager by the end of April.

NEXT STEPS

Finally, I’d rather not play this game alone – that’s why I’m sharing this process transparently. If you’d like to follow along, get involved or just clue me in on what I'm missing or doing poorly, you can reach me here. I’d welcome feedback and collaboration.

Next up I’ll recap and integrate sessions three and four: Developing a marketing plan + The fan data goldmine: Building a bulletproof fan CRM.

Until then, here's to you Mariah 🥂

lead image: Julie Knibbe