Spotify’s not just playing music anymore. They’re playing you.
Spotify once felt like the go-to place for discovering music that fit your mood or introduced you to something unexpected. Now, instead of fresh tracks, users are getting endless loops of rain sounds and ambient filler.
As it turns out, this isn’t a fluke. According to former Spotify execs, it’s a deliberate strategy to cut costs and boost profits, even if it means watering down the music experience.
Users Report Deteriorating Playlist Quality on Spotify
Spotify earned its reputation by making discovery feel personal. Playlists seemed to understand not just your taste, but also the timing to deliver music you didn’t know you wanted until you heard it.
But, that magic is wearing off.
More and more Spotify users report that the platform’s personalized recommendation features have deteriorated significantly in both quality and relevance.
“Over the last couple of years, Spotify has met my needs less and less,” shared one user.
“It’s not really reflective of my listening behavior as much as it is reflective of what they want me to listen to. It’s just a listening machine at this point, not a music platform.”
As expected, frustration is building across forums and social media.
For instance, Release Radar, which was designed to deliver new music based on listening preferences, now frequently fills with rain recordings and nature sounds instead of relevant music. Users describe how their playlists suddenly go from familiar artists to a succession of rainstorms, ambient noise, and brown-noise frequencies that bear little relation to their actual music preferences.
Discover Weekly has similarly degraded in quality, often delivering songs that users have already played or that poorly match their musical tastes.
Some users call it “AI garbage,” others say Spotify just doesn’t know them anymore.
In fact, even artist playlists have been invaded by tracks and entire albums from fake artists.
Former Staff Expose What Caused These Changes
Former Spotify executives and data specialists attribute these issues to deliberate business decisions that prioritize automation and cost-cutting over quality curation.
Doug Ford, a former Spotify executive who oversaw editorial playlist curation from 2013 to 2018, witnessed the shift firsthand. According to him, as Spotify prioritized profit, the editorial touch that once defined its playlists was phased out.
“That mix of the intentional algorithmic and human curation to make a really deep product was great,” Ford said, referring to Spotify’s earlier approach.
“The culture changed because it had to become a business. You need to be a successful business in order to offer this utility to people. But they’ve discarded some of the human aspects of it, for sure.”
Ford explained that things started changing in the lead-up to Spotify’s 2018 IPO as the company faced pressure to prove profitability potential to investors. During this period, he watched with dismay as the platform became flooded with generic mood music.
Since then, Spotify has leaned even further into automation.
By late 2023, the editorial curation team had shrunk to less than a third of the size of the algorithmic curation team. After layoffs in December 2023 that slashed 17% of Spotify’s workforce, the editorial team reportedly dropped to around 130 people.
As Glenn McDonald, Spotify’s former data alchemist who built Spotify’s genre classification system, explained:
“The genre system was human-guided. After they laid me off, they replaced it with a system that is not human-guided. It’s just machine learning. It looks at patterns of words in the titles and descriptions of playlists. That’s objectively worse.”
How These Changes Boost Spotify’s Profit Margins
Spotify’s recent cost-cutting moves have a clear financial payoff. By flooding its playlists with what insiders call “perfect fit content,” the platform cuts back on royalty expenses while boosting listening metrics that impress investors.
As more listeners use Spotify for “chill vibes” playlists and background music, the company realized it could reduce royalty costs by populating those playlists with inexpensive content.
This type of content includes royalty-light audio like rain sounds, ambient noise, and generic mood tracks. The kind of filler that’s cheap to license and keeps users streaming for longer.
This strategy serves dual financial purposes:
- First, it directly reduces licensing costs as these generic tracks typically come from unknown sources with more favorable royalty terms.
- Second, ambient sounds and mood music tend to keep users engaged for longer periods, boosting the platform’s “time spent listening” metrics that impress investors, all while costing Spotify less per minute than popular music from major artists.
And, while Spotify’s bottom line benefits, users are left frustrated with playlists that feel less curated and more like endless background noise.
The Ripple Effects of Spotify’s New Strategy
The financial impacts of these changes are evident in Spotify’s improved performance metrics.
From Wall Street’s perspective, the company is “killing it” as year-over-year numbers for subscribers and revenue continue to grow. These statistics, rather than user satisfaction or recommendation quality, have become the primary indicators of success in investor presentations.
However, as the platform leans into ambient sounds and generic mood tracks, lesser-known artists struggle to compete. Playlists that once introduced fresh indie acts now feature endless loops of rainstorms and white noise, crowding out genuine music discovery.
So, many artists find themselves competing with algorithm-generated filler that’s designed to keep listeners streaming for longer without paying out substantial royalties.
The ripple effects also extend beyond Spotify.
As the biggest streaming platform reshapes its playlists to maximize profits, it influences what gets made and what gets heard.
For instance, TikTok’s growing role in shaping music trends further complicates things. New music now often gains traction through TikTok before landing on Spotify playlists, creating a cycle where discovery happens elsewhere and Spotify simply follows the lead.
Basically, discovery isn’t the platform’s focus anymore—it’s a byproduct of someone else’s algorithm.