This illustration of Pandora's Music Genome Project can help clue him in.

Pandora helped take indie band Bronze Radio Return's career to the next level. But how does this happen? How does the Music Genome Project break a band?

Here's one common example.

One of Bronze Radio Return's singles found its way onto Mumford & Sons radio. That not only means serious exposure, but increased serious exposure in front of the right sets of eyes and ears. Pandora's experiment worked and paid serious dividends -- way beyond royalties -- for Bronze Radio Return. It came about because of the MGP's unparalleled precision.

Full-time, highly-skilled music analysts (musicologists, PhD types, actual musicians, etc.) score every song Pandora inserts into its catalog on dozens of attributes related to each song's musicology.

It's a complex list of variables covering everything from instrumentation to rhythm and beyond into the type of minutia you really need to be a music expert to understand. While Pandora adjusts its playlists to be culturally appropriate and smart, these subjective factors do not influence the MGP algorithm. The music you hear when you listen to Pandora includes, as Cue puts it, "songs that you would really like" and selections designed to help you discover tracks you might like. And it's done song-by-song on the basis of the actual song, not simplistic formulas that only take into account obvious and, on their own, unreliable factors such as genre, era and popularity.

Bronze Radio Return made it to Mumford & Sons radio because the MGP identified one of its songs as sharing many of the same and some attributes similar to a popular Mumford song. In other words, the MGP rated the two songs in close proximity to one another on the basis of the complex structure of the song. That's why, in addition to getting the seemingly obvious tracks on Mumford & Sons radio (say, The Lumineers), you might get the equally as appropriate Bronze Radio Return.

When the MGP identifies relationships between songs, Pandora runs an experiment on a "small" sample of its audience, usually about 1%. That can mean a more than statistically robust one million users or so. Then Bieschke sits back and watches what happens ... in real time.

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