Record companies are tracking download and search data to predict which new songs will be hits. This has been good for business—but is it bad for music?
In 2000, a Stanford Ph.D. named Avery Wang co-founded, with a couple of business-school graduates, a tech start-up called Shazam. Their idea was to develop a service that could identify any song within a few seconds, using only a cellphone, even in a crowded bar or coffee shop.
At first, Wang, who had studied audio analysis and was responsible for building the software, feared it might be an impossible task. No technology existed that could distinguish music from background noise, and cataloging songs note for note would require authorization from the labels. But then he made a breakthrough: rather than trying to capture whole songs, he built an algorithm that would create a unique acoustic fingerprint for each track. The trick, he discovered, was to turn a song into a piece of data.