Competitive Research Part 2

100DB • February 11 2019

100DB was a music discovery project I started. This is part of a series of posts I wrote to explore the thinking behind it.

Thanks to folks from the mailing list for letting me know I missed a whole bunch of platforms and functionality in my last sweep of music-recommending services. Here’s some follow-ups:


Spotify is the 800 pound gorilla here so it’s not surprising that folks had some thoughts. Specifically, I mentioned in the previous Research post that I didn’t have any social accounts connected to Spotify, so I was lacking that signal. A couple people informed me that Spotify almost certainly doesn’t use any friend/social recos. Instead (and apologies for over-simplifying the technical explanation) they’re basically running smart diffs on my plays and playlists, and community playlists that contain some of the same tracks. They’re ignoring fuzzy concepts like ‘genre’ and instead, essentially, filling in the blanks with stuff I might have listened to, had I known about it. Neat!

Expanding on that: human curation plays a not-inconsiderable role for Spotify – their recommendations feel human-like because they incorporate human intelligence in the chain. That’s expanded on in this 2015 article from The Verge, which is very much worth reading in its entirety, but this part in particularly grabbed me:

It’s still humans who are doing the song selection and arranging, but instead of outside experts, it’s users like you and me. Generating a human-curated playlist for each of Spotify’s users would be a challenge of mammoth proportion. “We probably can’t hire enough editors to do that,” says Ogle. So Spotify uses each of its users as one cog in a company-wide curatorial machine. “The answer was staring us in the face: playlists, since the beginning, have been more or less the basic currency of Spotify. Users have made more than 2 billion of them.” In effect, Discover Weekly sidesteps the man versus machine debate and delivers the holy grail of music recommendation: human curation at scale.

In a sense, this is reassuring – I don’t know exactly where I’m heading with this project but I do believe whole-heartedly in the human, rather than purely algorithmic, capacity to delight. Good to know that Spotify does, too.


Despite my previous claim that Soundcloud doesn’t have a recommendation feature, it does, apparently! But: it obviously doesn’t have enough info on my likes, dislikes, or listening patterns to make suggestions more depthy than ‘charts’ and ‘moods’. I don’t maintain a personal Soundcloud account, so it’s unsurprising that they can’t piece together any kind of profile of what I might like. I’ll give them props for surfacing a big collection of exactly the kind of content that I basically visit Soundcloud for: DJ mixes.


If I’m being honest I don’t really know a lot about Mixcloud. On first blush, it’s basically a Soundcloud-alike. I don’t have an account, so I’m not sure what kind of recommendation engine might be running under the hood. They do seem to be focused largely on DJ sets, and have a deep set of tags to drill down into specific genres and sub-genres. I found something I enjoyed listening to within three clicks, so the discoverability here is pretty dang good.

I also want to highlight Mixcloud’s ‘player’ functionality, which is doing three clever things I haven’t seen anywhere else: if I’m listening to a track, I can hover on the play button of another track to get a short preview. As soon as I lift off, I’m right back to where I was in the original track. The player itself keeps a history of everything I’ve been listening to – a kind of built-in visual bookmarking (without logging in!). Finally, as soon as I’ve listened to enough music to create some kind of minimal profile, it pops up a suggested next track right in the player itself. Good product thinking, Mixcloud team!


If Spotify is the 800 pound gorilla, Apple Music is the 650 pound gorilla. The website for Apple Music shows me extremely nice screenshots of Apple Music being used on extremely nice Apple hardware, which is pretty telling. It’s also (still) running Beats 1, essentially a live radio station, which strikes me as distinctly un-Apple – an appendix-like remnant of their acquisition of Beats. Apple’s evidently the more popular service in the States (vs. Spotify), but I don’t know anyone who’d recommend it as qualitatively ‘better’, per se.

The thing I really want to dig into vis-à-vis Apple’s music efforts is Ping, a service that operated for two years before being shut down. It seems like it was ‘music discovery via social networking’ . Nearly all of the platforms I’ve been digging into in these posts tend to eschew social networking in favour of straight-up delivery and various flavours of recommendations – but there’s something really compelling (to me) about a person-focused feed.


Why does Google have Google Play Music and Youtube Music? Re-read my lukewarm take on ‘Youtube Music’, this is the same animal with different stripes.


I forgot to mention Turntable in my ‘platforms I’ve never used’ section from the last post, and I bring it up now as it’s worth taking a peruse of the ol’ Wikipedia on this one – specifically “On November 22, 2013, it was announced that would be shut down in December 2013 in order to focus on its Turntable Live service, which allows musicians to perform interactive online concerts.” They shut down altogether a month and a half later.

I think Turntable is incredibly interesting for two reasons – the first being the recreation of real-world behaviours in virtual space, e.g. “If a user decided to click the “awesome” button, their character began to sway their head back and forth, simulating how a fan would react to a song they liked in a club.” There are very few instances I can think of where a 1:1 mapping of real-world action to an app action makes sense. (Successful uses of this are widespread in music production rather than listening.) That said, digital-only proxies for real-world interactions are emerging, like the real-time emoji reactions on Facebook Live.

Secondly, ignore everything I just said, because Marshmello performed a concert inside Fortnite last week. “By one (unsubstantiated) estimate, 10 million concurrent users attended the show in the game’s Showtime mode.” Turntable could clearly envision this weird future we live in, but couldn’t quite get there. What does any of this have to do with 100DB? I have no idea, except perhaps a reminder to think more ambitiously.