In Post-CD Era, Gracenote Makes a Big Business of Content Recognition
For Gracenote, the media database company, Christmas used to be the busiest day of the year. They called it “iPod Day,” because that was when millions of people would be unwrapping their new iPods and then rushing to their computers to rip dozens of CDs so they’d have some music to play.
For every ripped album, Apple’s iTunes software would contact Gracenote’s database, which would run the music through its audio recognition system and send back track and artist names and cover art.
“We’d see these massive spikes, three times or four times the regular load,” Gracenote CEO Stephen White says. “We had to architect the whole service so that we could support Apple on that one day.”
Sales of iPods peaked in the U.S. a long time ago—back in 2008—and CD sales have been plummeting for years as device owners have turned to direct MP3 downloads from online stores or streaming services like Pandora or Spotify. But the history that White is recounting isn’t as ancient as you might think. It wasn’t until 2010 that Gracenote’s Christmas rush began to abate, he says.
That’s mostly thanks to globalization. “As iTunes has come to Korea and Russia and India, you have a tremendous number of new consumers going through the same evolution,” White says. In other words, people outside the U.S. and Europe still buy most of their music on CD, and still need to rip it and run it through Gracenote. “Globally, the CD recognition numbers have started to flatten out, but they have not started to decline yet.”
Still, the CD is a dying format, and White says Gracenote isn’t counting on revenues from its music fingerprinting service to buoy it forever. Unbeknownst to most consumers, the 350-employee subsidiary of Sony has spent years building up other businesses. It has large divisions that work with TV manufacturers, cable networks, and other content distributors on video recognition technology, and with automakers on systems that help drivers use voice commands to navigate their music playlists. Last year the company exceeded $100 million in revenue for the first time.
Behind everything there’s still Gracenote’s massive database of 130 million songs and more than 1 million movies and TV shows. But these days, the lookups against that data are coming from hundreds of types of devices, from smartphones to smart TVs to set-top boxes to in-car entertainment systems.
In fact, the Gracenote service handles 10 billion queries a month—which, if it were a search engine, would make it bigger than Bing (but not quite as big as Google).
“We see ourselves as the underlying knowledge base that links together all of these various fragmented music and video assets all over the world,” White says. “So ultimately, yes, we do understand that the CD will go away. And we have built a diversified business to allow us to add value in other parts of the ecosystem and make up for it over time.”
I visited Gracenote’s headquarters in Emeryville, CA, just as executives were getting ready for the International CES show in Las Vegas, and got a survey of its historic offerings as well as a bunch of edgier projects that show where the company is going in the near future.
Just look at Gracenote-powered apps like Habu Music—which lets you browse your music collection according to the mood you’re in—and it’s clear how far the company has grown beyond its origins in the early 1990s as the Compact Disc Database (CDDB), the first large collection of disc names, track names, and other metadata about the music files on CDs.
“A lot of folks think of us as a metadata company, but we are really not,” White says. “We are a technology company that happens to have a tremendous amount of metadata.”
Still, at the core of the business is the care and feeding of Gracenote’s media databases. Record labels, artists, publishers, and movie and TV studios submit more than 100,000 new songs and videos to the company every week, and a large editorial team at Gracenote does nothing but curate and enhance this data.
There’s software that creates a fingerprint for every file, and plenty of machine learning algorithms to help describe elements of the submissions, such as their mood and tempo. But humans are needed to … Next Page »