Spotify just announced Jam, a new collaborative listening experience for its users. 

And while this seems exciting on the surface, it’s important to recognize that Spotify has a long and checkered history of not knocking this sort of thing out of the park. 

Solving these problems is important for us both as listeners and as artists because the more bot issues the platform faces, the less effective Spotify’s discovery tools are for everyone. 

So the question is: can Jam solve some of the early problems Spotify has faced within its community listening features? 

Well, let’s take a walk through the history of group listening on Spotify to find out. 

The Collaborative Playlist problem

When Spotify overhauled its Collaborative Playlist feature in 2020, the streaming giant billed it as “a great way to swap podcast recommendations, share your latest music discoveries, and build the perfect playlist—together.” 

The problem is, this isn’t exactly how it played out for many people. 

Sure, there were users who found value in the updated collaboration features, but those were the fortunate few who set their playlists to “private”. 

But for many with publicly available playlists (read: anyone can join) bots quickly became a problem. 

Overnight, listener upon listener found their long-time, meticulously curated playlists wiped clean and replaced by a ton of foreign music they’d never heard of. 

Now, as artists, we’re all fully aware of the bot problem on Spotify (just pay to be on a playlist and you’ll see), but to the average listener with no experience on the artist side of the platform, this was a new revelation. 

And, as is generally the case, it only took a few bad actors to destroy something that started with the best of intentions. 

To account for this, Spotify pivoted and launched Blend.

Blend gets it right… sort of

With Blend, Spotify built a pretty ingenious product (IMHO), which allows you to combine your data with friends, family, or even your favorite artist to algorithmically generate a shared recommendation engine based on your collective listening history. 

Pretty cool. 

In doing so, Spotify removed that pesky bot problem they had experienced with Collaborative Playlists (or at least minimized it). 

In essence, by algorithmically generating the playlist, Spotify retained more control over the content in the queue and who could add it. 

But it wasn’t a perfect replacement for collaborative playlists. 

Enter: Jam. 

Spotify unveils Jam

Spotify recently announced Jam, “a new, personalized way to listen with your entire squad.” 

Kinda sounds like Collaborative Playlists to me. 

And Blend. 

But also… not. 

Jam seems to pick up where Blend left off while re-adding some of those personalized features that fell off from Collaborative Playlists. 

Not only does Jam serve as an algorithmic suggestion engine, but it also allows members of the Jam to add their own tracks as well. 

In fact, the recommendation engine is based on the music existing members of the Jam add to the queue. 

That’s good stuff in my book. 

And on top of that, Spotify seems to be taking the security of actually creating and sharing a Jam quite seriously. 

Adding another Spotify user to your Jam requires a direct link, Bluetooth connection, or the scanning of a QR code. 

So, assuming you don’t make any of these three things publicly available, it sounds like Jam may actually pull off Spotify’s long-desired feature of creating a truly customized and algorithmically combined collaborative listening experience for its users. 

If it works, this is great news for artists. 

Better discovery means better fans. 

That is, until the bots get ahold of it, of course.