by Angela Guess
Bernard Marr recently wrote in The Huffington Post, “Technology and music are bedfellows again – though the fat cat record company execs smoking fat cigars have been replaced by coffee-sipping tech whiz kids. And Big Data and analytics have played a big part in this reinvigorated romance. From recommendation engines designed to choose the perfect individual playlist, to Internet of Things enabled pop concerts, data is redefining the dynamics of the music industry, as well as the relationship between listeners and music, in ever more creative ways. In the past, the record industry had relatively little way of understanding who was buying their LPs, cassettes or CDs. Downloading allowed them to begin tracking listening habits and making recommendations in the same way that Amazon does for books. With the current streaming model, however, the floodgates are open, with detailed information about when, how and where we are listening all up for grabs.”
Marr goes on, “The industry’s aim now is to combine this deeper understanding of its customers with the deeper understanding of the music itself, which Big Data has also made possible. Raw music is essentially unstructured data but because it is easily digitized, it can be quantified and analyzed. Since 1999, the Musical Genome Project has been structuring music data by manual classification as well as automated algorithms. Up to 450 data points are collected on every song in its database – currently around 30 million. These include factors such as the gender of the vocalist, the instruments in use, the speed of the rhythm and the style of backing vocals. Each track is studied by a specially trained musicians, much the same way as Netflix employs people to watch films and classify their content. By structuring the unstructured data of raw music, tracks can be compared with each other and judgements made, algorithmically, about what a user might want to listen to next.”
photo credit: Pandora