The music industry has needed a face-lift for a long time. Luckily, the advent of big data might provide musicians with a more successful revenue model. This represents one of the biggest industry shifts that music has seen in decades. Let’s explore the possibilities big data currently offers the long-suffering music industry.
A New Revenue Model
The entire revenue model of the music industry has changed in the last decade. Although streaming sites like Spotify helped curb online piracy, the music industry hasn’t yet clearly defined the royalty rates for streaming music.
Big data might change that, because it helps bring artists and corporations together more effectively via high speed data analysis such as a Hadoop cluster. Data from streaming sites provide companies fantastic insights into the genres and styles their target demographic currently likes.
Although there’s a long-raging debate about “selling out”, it’s starting to look like a big data-backed strategy might be the last refuge to get musicians paid.
The Failure of Subscription Services
YouTube recently unveiled their long-awaited subscription music service. It’s a move designed to improve what some describe as their “absolute advertising overkill“. Analysts are critical of this move–it certainly didn’t work for Pandora or Spotify (not to name dozens of other services).
Big data analysis is revolutionizing the way businesses choose to connect with their target demographics, and soon, the music industry will likely follow suit.
By utilizing new ad technologies and social media platforms, the music industry may figure out how to get a bigger digital advertising sector they can leverage into exciting new collaborative marketing with big brands. Among those already on board are Nike, Urban Outfitters, and Red Bull.
This means that musicians and record companies may adopt the type of revenue-sharing model utilized by social networks like Instagram.
Instagram’s popularity as a marketing tool has exploded in the last few years. Currently, it’s considered one of the highest-engagement platforms. Through tastefully-chosen advertising, artists are getting to share their work and brands get to promote awareness. The music industry might follow in their footsteps–and big data could play an important role in the switch.
It may not be long before music videos and even entire albums are sponsored by corporations.
How Big Data Can Change Music
Big data provides information about listener motivation–why do they listen to a specific artist? This helps the industry spot trends faster, and provides accurate data about a demographic’s unique “musical dna“.
It will also provide the industry with better fan engagement strategies, made possible by relationships between innovative artists and brands. This could solve many current industry issues with music distribution.
Perhaps most importantly, streaming music via a big data catalog may solve the problem of artist compensation. Many are pushing to get artists paid by their number of “plays”, similar to pay-per-click advertisements.
The music industry now accepts that many people won’t pay for music. Big data advances might facilitate an important change, taking pressure off of consumers to fix the music industry’s outdated revenue models. After all, songs are data.
Over time, a gigantic “store” might be created out of this massive collection of data.
Artists will be able to opt into data revenue sharing–providing more control of the direction of their art.
Will Musicians Go Along?
There’s a lot of stigma about “selling out“. However, many savvy artists realize that, like other tradespeople, they need to collaborate with businesses to accomplish big goals. The big data solution is right in front of the music industry, and for once, it seems like the music industry might be ready to make some much-needed changes.
Big data can improve monetizing strategies, marketing, and the seemingly bygone notion of artists making a sustainable living from their music. Above all, big data may improve music’s primary function: bringing people together.