How The Music Industry Uses Data Analytics To Pick Stars

This Atlantic article examines the Shazam Effect, the music discovery app that collects data on what songs people want to identify. The data Shazam has amassed provides insight for music industry insiders to artists on the rise.

To quote the article:

By studying 20 million searches every day, Shazam can identify which songs are catching on, and where, before just about anybody else. “Sometimes we can see when a song is going to break out months before most people have even heard of it,” Jason Titus, Shazam’s former chief technologist, told me. (Titus is now a senior director at Google.) Last year, Shazam released an interactive map overlaid with its search data, allowing users to zoom in on cities around the world and look up the most Shazam’d songs in São Paulo, Mumbai, or New York. The map amounts to a real-time seismograph of the world’s most popular new music, helping scouts discover unsigned artists just as they’re starting to set off tremors. (The company has a team of people who update its vast music library with the newest recorded music—including self-produced songs—from all over the world, and artists can submit their work to Shazam.)

The fact that music fans are having a direct say in what artists gets promoted highlights the importance of musicians developing a direct relationship with their fans and an understanding of how to inject their music into systems such as Shazam’s. Shazam provides its own instructions, but different services likely have their own requirements.

This video from The Atlantic discusses some of the downsides of such data mining practices:

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