Discovering vs Exploring – Tools for the Future of Music Streaming

Naveen Chopra, former interim CEO and CFO of Pandora as reported by MusicAlly:

“We believe that the primary listening experience is passive, for most people, meaning 90 percent of the time you just want to listen to music you like,” said Chopra. “It’s not about picking songs you like and building playlists.”

Gustav Söderström, Chief R&D Officer of Spotify, also by MusicAlly:

“Today we have over 200 petabytes of music data,” said Soderstrom. “We believe that with our larger user base and our higher user engagement, the distance to the competition is actually only increasing… Already today, we have more than five times the amount of music data that our nearest competitor does.”

He even compared music-streaming to the world of self-driving cars, where the more vehicles a company (like Google, or Uber) has out on the roads generating data, the better its chances of success in the long-term.

“We have by far the most cars on the road in terms of users, but importantly they’re also driving more hours a day than anyone else, so more miles. And we’re putting more cars on the road every day, because of our free tier… This is self-driving music!”

For all the success that streaming services have been having in making algorithmic, editorial and algotorial recommendations, I personally believe that they are neglecting the development of tools better suited to more advanced users. 

To use concrete examples, these tools could serve to allow the user to easily listen through the content of a book like “1001 Albums to Listen Before you Die”. Or to explore one or more lists of the best albums of any given year. Or  offer some slightly more robust “queue” tools to plan for an upcoming party or car trip. Or a better way to collect, group and go thru all songs that are recommended to them on social networks and newsletters.

As I detailed in the previous link about “1001 Albums”, on a most basic level one tool could be a “bookmark” to let you know where you stopped on a playlist. Or tick marks to know which songs from it you have listened. But on a larger sense this tool is about embracing new concepts, like  ‘anthologies’  and integrating them on the service in a practical way.

I sense an opportunity here. The number of “power users” who would value these kind of features maybe small, but 1% of a few hundred million people is still a few million people. They may even be more valuable than average users.

Platforms mature and so the users. Perhaps after a few years of using the app, perhaps an increasing number of average users will be increasingly ready to use such tools. 

And then there are second order effects. Who knows how these tools will look like a few years down the R&D road?  What new use cases and possibilites will they allow? How much of the tools will trickle-down to new features that every grandma will depend on daily? 

Finally, I suspect that the real number of active listeners are being severely undercounted. What if a majority of the very average users are in fact power users some part of the time?

Maybe the need for such tools of music exploration and organisation would arise only once a month or a year, but that would be a huge amount of use too.

Because the truth is that many people care a lot about music, even if they don’t admit so. How common are such habits as reading album reviews and popstar profiles, attending music shows, wearing band t-shirts, even watching two hour music documentaries?  These are all ways of actively engaging with music. Heck, how many copies of “1001 Albums to Hear Before You Die” have been sold and read over the decades? 

Maybe the demand for the tools is there, widespread but latent.

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