Next Big Sound’s Victor Hu On YouTube Replacing Radio & Labels Ignoring Likes

From Hypebot:

Hypebot stopped by Next Big Sound’s New York office for a chat with its data scientist Victor Hu, formerly a mathematician for the U.S. Department of Defense and “stats whiz” for the New York Yankees, to see how the company gauges music popularity for clients including Billboard, which relies on Next Big Sound for one of its charts.

The short story: Next Big Sound measures how popular an artist is in a number of ways, then looks at how fast they are accelerating, and then looks at the acceleration of that acceleration – a concept that might make more sense if you remember your high school calculus. Also, if you’re trying to figure out how popular a musician is, Wikipedia will tell you more than Facebook.

I pulled some key nuggets from our interview to try to distill how Hu does what he does, so that we mere mortals (i.e. normal people for whom high school calculus memories is the closest we normally get to this sort of thing) can try to grasp it.

Public and private data mashed together

“I take all of this rich data that we have — it’s essentially three years of any kind of data you would want to know about an artist, both public and private,” said Hu. “I’ll look at all the major social media networks combined with private sales data, radio, and concert data — basically for every artist. We’ve been tracking this for a long time, and my job is to take [the data] and glean intelligence from it — turn it into insights that we can recommend to our customers… for example, the Billboard charts.”

By public sources, Hu explained that he was referring to Next Big Sound accessing APIs from a number of sources (the site lists Facebook Insights, Google Analytics, iTunes Upload, Twitter, Facebook, YouTube, Vevo, Wikipedia,, ReverbNation, SoundCloud, Pandora, Vimeo, Rdio, MySpace, and Instagram).

But what private data sources is he talking about? Well, it’s some of the same numbers Billboard relies on for its other charts, just analyzed differently, and mashed against other sources.

“Private is something like sales data,” added Hu. “There’s no way to get access to that unless you have a relationship with them, which we do. We’re getting it primarily from the labels themselves. The labels who are our customers, they want to see all of their sales numbers in conjunction with the social media numbers, and so they give us this data, so we can put it into our dashboard, and they can see it and slice it in any way they want to.”

It Watches YouTube Replace Radio as a Sales Driver
“We were asked to do a case study for one of our clients on a particular artist,” remembered Hu. “He was doing very well with — his sales numbers just took a spike. It wasn’t in the presence of strong radio play, so that’s very unexpected, given how artists normally progress — if you come out with a hot song, that’s what triggers a lot of your sales. They couldn’t figure out why that was, and they had us look into it more. We followed the rabbit hole down, and it turns out it was because he had released a new video on YouTube right around the time of his spike. That in conjunction with his appearance on an award show — you could see the clear shape of his increasing digital sales come right after the release of his music video, which is not, I think, intuitive… to see YouTube tied so closely to sales was, I think, very encouraging.”

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