Spotify.Me is par for the course when it comes to the streaming company’s public-facing analytics. It offers intriguing, if unintentionally hilarious, depictions of recent listening. The widget ends with a marketing call-to-action, so despite the presentation, this seems like less of a fun toy for the casual listener and more of a resource for marketers. In parsing my own analysis, however, the results reflect both the power that Spotify’s big data algorithms can wield and the potential flaws to such a system.
For instance, 60% of my listening was classified as energetic. But two of the sample tracks it chose to highlight this trait stemmed from when my niece visited and played DJ with my account. I was also dubbed an eclectic listener, with genre choices all over the place. And that’s accurate, but it’s partially accurate because Spotify isn’t my sole listening platform. I have some meticulously crafted playlists and I enjoy the recommendation engines, but I also maintain a large music collection in iTunes and on vinyl. So my data is just a partial snapshot of my listening, and thus probably not the best reflection of the marketing focus groups I would best represent.
But it’s unclear how Spotify is drawing its conclusions in the report. It’s hard to see why people who prefer playlists made by others are more likely to put in long sessions at the gym, or why people who stick to their favorite artists would be more likely to purchase energy drinks. That’s not to say there isn’t a vast trove of data here that marketers and advertisers would bend over backwards to get. But the application of that information in how and when advertisements will influence listeners seems to need a little finessing yet.