Skip to main content

How big data can change the music industry

Join us in Atlanta on April 10th and explore the landscape of security workforce. We will explore the vision, benefits, and use cases of AI for security teams. Request an invite here.


The topic of royalty payouts from streaming services emerges year after year. The arguments remain the same, yet no progress has been made.

Industry leaders continue to focus on streaming royalties as the only future of artists’ revenue. As of yet, the fate of music monetization remains undecided. Some argue the goal is — and always will be — to simply get artists’ music in the ears of consumers. Others seek to continue getting consumers to pay for music. Still, it’s unlikely that subscription models will be the only answer to how music creators, both signed and independent, get compensated for their art in a sustainable way.

Total music sales in the U.S. have dropped below $7 billion compared to $13 billion in 2003, according to the RIAA. Meanwhile, led by the technology industry, the music industry continues to replace old, classic pay revenue models like CDs and iTunes with newer models with shrinking market shares.

Nielsen recently investigated the future of the music business and exposed the unfortunate reality of consumers’ purchasing habits. Namely, labels that choose to remove an artist from streaming services may squeeze out eight percent in extra sales, though they may be training the remainder of listeners to look elsewhere for that artist’s songs. Most often, this results in illegal downloads. What music really needs is a diversity of revenue opportunities beyond pure consumer models like subscription and sales.

And what I believe is fundamentally missing from the debate is a new revenue source for music: Big data.

Connecting with the audience

Music is the one universal media that connects the world, and big data is the key to unlock its potential. Not only does data have the potential to make up for the revenue lost from physical sales, it can actually surpass it. Through ad tech and social media, music can leverage a much larger, data-driven digital advertising market and join the global trend toward collaborative marketing and mobile engagement for brands like Redbull, Nike (Nike+), and Urban Outfitters.

Music influencers are already arguing for a redesign of the industry’s approach to advertising. “When commercials stop being advertising, they can be art,” said actor, director, and musician Jared Leto at a recent round table discussion for Adweek.

However, current music services are monetizing at surface-level, focusing only on what people are listening to and where they are listening. YouTube recently launched their highly anticipated subscription-based music service essentially to solve their advertising overload problem, which isn’t scalable. How many more ads can YouTube possibly fit into those screens? But by moving into the subscription space, they are taking a huge step backward toward what hasn’t worked for Pandora, Spotify, Rdio, Beats Music, and others. Streaming revenue margins don’t improve with scale, and it doesn’t look like subscription models will compensate artists in a fair manner anytime soon.

It seems music needs an entirely new way to connect with consumers. Let’s consider a revenue share model, using Instagram as a case study.

In the past two years, Instagram has exploded as a marketing and advertising tool for brands. Companies have experienced a higher percentage of engagement on Instagram than on any other platform, and last year the social networking tool launched integrated, carefully placed advertising that meshes seamlessly with users’ news feeds. Perhaps more interestingly, brands have explored collaborations with popular Instagram influencers as a means of connecting with their target demographic. Suddenly, freelance photographers and social influencers are making a living by sharing branded content with their audience. Beyond blatant banner ads and monthly subscription fees, brands have found a way to organically connect with their consumers.

The same concept may be on the horizon for the music industry, especially if it’s grounded in big data. Since big data can reveal consumers’ motivation behind their music choices, connecting social context with its consumer behavior, data can also reveal the “music DNA” for specific demographics. In other words, these are the combinations of music that appeal to groups of listeners. This can inform powerful engagement strategies and enable artists to offer data of tremendous value to brands.

“The velocity, volume, and variety of data associated with music, listeners, and music influencers present a huge opportunity to extract meaningful insights that can deepen user customer engagement, fueling new business models and creating data-driven brand awareness,” said Wilson Cheng, my fellow cofounder at weeSPIN.

A catalogue of big data

Much like Instagram with sponsored posts, brands can use data and music DNA to drive engagement strategies that strengthen awareness and loyalty. Combining this with a proper distribution platform, brands have a powerful tool to support any ongoing campaign efforts. In turn, artists can receive fair compensation based on their own engagement with their audience, and each song played via brand channels (i.e. Playlists, stations, etc.) can generate revenue like clicks.

Instead of relying solely on consumers to monetize their music, artists can monetize by helping brands connect with their target audience. The potential is endless, since data is not limited by the rigid structures of the old music industry regime. There is a lot of room to innovate.

Ultimately, the entire digital catalogue of more than 30 million songs can be translated into a big data store. Artists can choose whether they want to participate in this data revenue program, and soon they’ll be able to authorize their songs for data monetization through distribution platforms like Tunecore or my company, weeSPIN. Brands can pay for analytics through platforms like these to help build music brand profiles by selecting target demographics, territories, social interests, age groups, and so on. Calculation of revenues will simply be based on total songs played or clicked (i.e. a song suggested by Nike for workouts) within any ongoing campaigns. This allows artists of all sizes to monetize directly from brand engagements generated by their songs, without mixing their art form with distracting audio or rich media ads.

One might argue that a brand data model is flawed based on the massive scaling necessary for enough demand from brands to sustain the music inventory supply. And not every brand is a good fit for music or music-branded marketing. However, the trend of content advertising is undeniable. Native advertising is one of the fastest growing segments of the advertising market. Agencies like Anthemic are jumping on the content publishing bandwagon to establish their own content creation outlets like Flood.

So let’s ask ourselves: Why not music? It’s the most social of all our media options with massive penetration and the most loyal tribe. Realtors can partner with lifestyle brands and architects. Credit card companies can build small business inspirational brands. So why shouldn’t brands partner with music? The opportunities are limitless. If massive scaling is what’s required, let me be bold in stating that data monetization could witness the fastest growing era in music’s history. Only this time, artists are in charge.

Darius FongDarius Fong is a music entrepreneur and a Grammy Award-winning audio engineer who produces music as thePREFCT. He graduated from Indiana University of Bloomington with a bachelor’s degree in telecommunications. His production credits span from rock bands like Weezer and Cold War Kids to jazz legends like Herb Alpert, Sergio Mendes and Natalie Cole. In 2013, Darius founded weeSPIN, a social networking app that connects music through people’s social and daily habits.

VB Daily - get the latest in your inbox

Thanks for subscribing. Check out more VB newsletters here.

An error occured.