“Hit Song Science” became more popular after Michael Lewis’s Moneyball.
Of course it did.
Everything – having to do with statistics and big data – became more popular after Michael Lewis’s Moneyball.
(Such a good book.)
I find it fascinating that our brains almost instinctively know what it wants from a song – just like it does from a story.
And this the other Mike McCready. Not the Rock and Roll Hall of Fame, Mike McCready, of Pearl Jam.
Hit Predictor was only one of a variety of different approaches to anticipating hits that became popular following the publication of Michael Lewis’s Moneyball, in 2003. The gut decisions record men were famous for making were subject to crippling psychological biases and hurt profits. A safer approach was, for example, Hit Song Science, a term trademarked by music entrepreneur Mike McCready. Hit Song Science was a computer-based method of hit prediction that purported to analyze the acoustic properties and underlying mathematical patterns in a new song, and compare them to those of past hits. In a 2006 New Yorker article, “The Formula,” McCready told Malcolm Gladwell, “We take a new CD far in advance of its release date. We analyze all twelve tracks. Then we overlay them on top of the already existing hit clusters and what we can tell a record man is which of those songs conform to the mathematical pattern of past hits.” Not only that, McCready’s song machine could also tell a record man which aspects of the song needed to be remixed in order to make it a hit. It was all a question of giving the brain what it wanted from a song. “We think we’ve figured out how the brain works regarding music taste,” McCready declared.
-John Seabrook, The Song Machine