Predicting Music’s Next Big Stars Using Audience Affinity Data


UnnamedIn this piece we take an in-depth look at how big data, and specifically audience affinity data combined with careful audience insight can be used within the music business to predict the next big stars to rise to industry prominence.

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Guest post by Hannah Chapple of Affinio 

Don’t get left behind.

Learn how affinity data and advanced audience insights can predict the next big music star before anyone else.

Discovering and fostering new talent keeps the music industry alive, and everyone from A&R teams, management companies, live event promoters, streaming services, to brands and activation agencies are constantly looking for the next big thing. I mean, who doesn’t want to sign the next Carrie Underwood or discover the next Beyonce? That said, the goal for talent-seekers and those who risk their money on new talent is, of course, to find the next big thing before anyone else and ensure that the next big thing makes money and lots of it.

Fans access to music has drastically evolved in the digital age and so have the roles of the individuals responsible for finding and investing in new talent. By now we’re sure these teams are listening to social metrics, fan counts, and demographics and other sources to identify new, emerging talent. But today new technologies, big data, and audience insights are changing the game, and the teams with the best tools, curation, and expertise, win.

Without the right tools in your arsenal, music teams run the risk of partnering with artists that are either not profitable or resonating with the intended audience or even miss the chance to partner with an artist because they have already been scooped up.

“Big data is radically transforming the music industry.” – Dylan Love

The truth is, today you may not need to leave the comfort of your home to find the next big star. Unlike years past, it is not necessarily the live shows or underground buzz that get artists discovered, but instead their online presence. As shared byKernel, “Our online interactions with music are interesting to the music industry because each interaction yields valuable data about who we are and what we like.” While there have been success stories of teams scouring the internet looking for the next golden nugget or Justin Bieber, this process is time consuming, incomplete, and rarely repeatable without the right tools in hand.

The tools? Affinity data.

The smart music teams leverage affinity data, and immediately identify up-and-coming artists in an efficient, repeatable manner, and in a way that significantly raises the probability of success.

Affinity data provides an in-depth look at audiences including who they are and what they like. (Learn about affinity data and how Affinio identifies advanced audience insights, here.) Using audience intelligence and affinity data, music teams can identify a list of early stage developing artists that are already resonating with a set audience. These are the artists that are building a passionate following but have yet to break through as a “mainstream” act – these are the individuals that need to be on a talent seeker’s radar.

In essence, by leveraging affinity data, your ideal audience – fans – finds talent for you.

Let’s take a look at this use of affinity data.

Let’s say we are a music team looking to find new talent in the Country and Americana genre. To begin, I decided to analyze the audience of the Bluebird Cafe – a famous club in Nashville, Tennessee where many singer-songwriters have been discovered over the years (including Taylor Swift!) The Bluebird is a go-to spot in Nashville for singer-songwriters of this genre to perform. Using Affinio, I ran an interest-based segmentation analysis on anyone following the BlueBird on Twitter (@bluebirdcafeTN). The Affinio algorithm then compiled all of the unique people following the Cafe and began to analyze each of their following patterns. The algorithm then matched people with similar interests and grouped them into interest-based clusters.

Here’s what this looks like:

Above is an audience visualization of the individuals following the Bluebird Cafe. As you can see, interest-based groups such as Nashville Locals, UK Country Music Fans, and TV Show “Nashville Fans.” (FYI – The Bluebird Cafe has been featured numerous times on the CMT show, Nashville.)

Within this audience, there are also strong interest-based clusters of Country Music Fans and Americana/Country Singers-Songwriters. Let’s explore the Americana/Country Singers-Songwriters.

As an A&R team, or any team looking for talent, we can validate that these individuals are singer-songwriters by their shared interests and how they self-describe.

Interests of the Audience

How the Audience Self-Describes

These individuals are our ideal audience. We can dive deeper and hone in on this particular community to find out who and what matters most to them and why. By understanding the culture of a community, music teams can quickly identify emerging artists already resonating with the audience who have built a small, but passionate following.

With Affinio you can sort audience interests by relevance or affinity. The Affinity Score is a calculation for how many times more likely this audience is to follow a given account as compared to the rest of the network; this helps music teams identify the strongest, niche influencers amongst an audience – or – the emerging artists.

Take a look at the influencers (sorted by affinity) that are resonating with this audience.

The individuals featured in this list are contextually relevant to this Singer-Songwriter community. For the purpose of this example, I am focusing on small-scale singer-songwriters who have built a following of between 5k-20k followers. While 5k-20k followers may sound like a lot, compared to big-name Americana/Country artists such as Kacey Musgraves and Elle King, these artists are still little fish.