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SBE 430 Week 1 Case Study


Pandora is the Internet’s most successful subscription radio service. In January 2011, it had over 80 million registered users in the United States, and continues to add about 600,000 new subscribers a week—that’s one new subscriber about every second! Pandora now accounts for over 50% of all Internet radio listening hours. Radio? In the Internet age of iTunes, Rhapsody, and listen-to-what-you-want-anywhere-anytime? Why would anyone want an online radio station to choose the music they will be able to hear? That’s so old school. Not exactly. At Pandora, users select a genre of music based on a favorite musician, and a computer algorithm puts together a personal radio station that plays not only the music of the selected artist but also closely related music by different artists. How does the computer know about closely related music and music genres? Can a computer understand music? Not really. Instead a team of professional musicians listens to new songs each day and classifies the music according to over 400 musical criteria including male or female vocal, electric vs. acoustical guitar, distortion of instruments, presence of background vocals, strings, and various other instruments. These criteria are used in a computer algorithm to classify new songs into five genres: Pop/Rock, Hip-Hop/Electronica, Jazz, World Music, and Classical. Within each of these genres are hundreds of sub-genres. Like Taylor Swift? Create a radio station on Pandora with Taylor Swift as the artist and you can listen all day not only to some Taylor Swift tracks but also to musically related artists such as Carrie Underwood, Rascal Flatts, Anita Nalick, and others. The algorithm used to identify genres of songs is a result of the Music Genome Project conceived by Will Glaser and Tim Westergren in 1999. Westergren, a jazz musician, and Glaser believed it was possible to identify genres of music, and sub-genres, using their expertise (and that of other musicians) to identify similarities among artists and songs. They have identified over 400 factors to help classify songs, and leave it up to the computer program to select appropriate matches based on a user’s input of a selected artist. To some extent they are mimicking disc jockeys and radio program managers who had no trouble creating jazz radio, classical radio, and pop/electronica stations, and within these general categories, sub-groups of musicians who shared musical characteristics. In 2005, Glaser and Westergren launched Pandora.com, a music service based on the Music Genome Project. Their biggest challenge was how to make a business out of a totally new kind of online radio station when competing online stations were making music available for free, most without advertising, and online subscription services were streaming music for a monthly fee and finding some advertising support as well. Actually, their biggest challenge was to avoid going broke: over 80% of online music is downloaded from P2P networks for free. iTunes launched in 2001 and by 2005 was a roaring success, charging 99 cents a song with no ad support, and 20 million users at that time. The idea of a “personal” radio station playing your kind of music was very new. Facing stiff odds, Pandora’s first business model was to give away 10 hours of free access to Pandora, and then ask subscribers to pay $36 a month for a year after they used up their free 10 hours. Result: 100,000 people listened to their 10 hours for free and then refused to use their credit cards to pay for the annual service. People loved Pandora but were unwilling to pay for it, or so it seemed in the early years. Facing financial collapse, in November 2005 Pandora introduced an ad-supported option. Subscribers could listen to a maximum of 40 hours of music in a calendar month for free. After the 40 hours were used up, subscribers had three choices: (a) pay 99 cents for the rest of the month, (b) sign up f


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