Pandora's Profit

Wired had a little blurb about Pandora finally turning a profit in 2010. This can be attributed to many things, such as the growing fan base, the iPhone application, and the addition of commercials. What's more interesting is that Pandora is essentially becoming the same thing as radio in doing so with a small quirk. First, the addition of audio commercials was a major step, not just in the profitability, but also in the precedent. If viewers continue to listen, it's very likely ads will increase in frequency. It appears that listeners are not against advertisements in general, but no one has come up with a limit before users turn away en mass.

Also, the iPhone application is essentially the same in functionality as a personal portable radio. The only real difference is that you are streaming radio from the web to your phone. However, you have marginal control over the content. Yes, you pick the artist and you can assign "thumbs up" and "thumbs down," but I would not say that this radio is truly personal. You have no direct control on novelty, artist frequency, repeats, etc.

I think what has worked best for Pandora is the perceived personalization. Essentially, users do not want to be dictated listening habits. There's also an inherit confirmation bias in any recommender system. I'll remember the hits and forget the misses or explain it away. Also, people tend to respond positively when someone says, "you'll like this." It's incredibly hard to come up with a controled test to measure effectiveness. Some researchers have tried, such as comparing lists of recommendations and asking which is man-made or machine-made. However, the goal of a recommendation engine is to build the one with the best recommendations, not to mimick humans. At best, we can compare how two engines perform by comparing the number of skips.

For example, we could compare Pandora and Last.fm in a large-scale listening test. Again, we need controls. Pandora and Last.fm differ in the amount of perceived control. Both Pandora and Last.fm do not give a lot of control on how music is played, but Last.fm allows more feedback. Both Pandora and Last.fm have access to a positive/negative vote for each song and initial seed song selection. However, Last.fm also allows for tagging individual songs in an effort to improve selection. Of course, this is legitiatimate; however, a real test would let users tag songs for Pandora, but then Pandora would just ignore the tags. In addition, users need to be blinded on how the process works. It's not a fair comparison if someone tells you that a system is based on machine interpretations of expert or wisdom-of-the-crowd ratings.

I'm glad that Internet radio stations that thrive on "personalized" recommendations are beginning to make a profit. However, it's a bit early to say that a new dawn of music has emerged. Promising, absolutely; but more research is needed.