How to find new music you'll actually like
Ask anyone how to find new music and you'll hear the same thing: use Discover Weekly, follow more playlists, let the algorithm work.
It's not wrong. It's just the shallow end.
Discover Weekly is a solid playlist — 30 songs every Monday, built from your listening patterns and collaborative filtering. Spotify says it drives 56 million new artist discoveries per week. For most people, that's genuinely enough. But Spotify also has over 100 million tracks, with roughly 60,000 more added every day. If you're relying on one 30-song playlist to keep you current, the math doesn't work.
There are four real approaches to discovering music. They go progressively deeper, and the right one depends on how you listen.
Algorithms
Spotify gives you three surfaces: Release Radar on Fridays (~30 tracks mixing followed artists with algorithmic picks), Discover Weekly on Mondays (fully algorithmic), and the Home feed (personalized daily). Apple Music, YouTube, and every other streaming platform have their own versions. Spotify even added genre-control buttons to Discover Weekly in 2025 — you can steer it toward up to five genres and regenerate the playlist on the spot.
They're all useful. They all share the same structural limitation: they optimize for engagement, not completeness. If someone you follow drops a full album, Release Radar gives you one track. If a producer you care about gets credited on something but isn't the headline act, none of these surfaces will mention it.
If your listening runs through underground scenes — club tracks, independent rap, small-label releases — algorithms are even weaker. Collaborative filtering needs volume to work. If not enough people are listening to something, the model can't recommend it. The algorithm doesn't surface what it hasn't learned to see.
Then there's the filter bubble. The longer you rely on algorithms exclusively, the narrower they get. They learn what you skip and double-save, then serve tighter variations of the same thing. Great for mood playlists. Bad for actually broadening your taste.
Use them as a passive layer. Let them run, take what's useful. Just don't confuse a recommendation engine with a discovery system.
Communities
Reddit has r/listentothis (18 million members), r/hiphopheads (3 million), r/indieheads (2.7 million), and r/electronicmusic (2.6 million). Smaller subs like r/LetsTalkMusic are less populated but often more useful — fewer memes, more actual discussion about why something is worth hearing.
The signal-to-noise ratio varies by community. r/listentothis enforces a rule against mainstream artists, which keeps recommendations genuinely obscure. Genre-specific subs tend to offer the best return on time — the weekly recommendation threads in r/electronicmusic consistently surface names that won't show up in any algorithm for months. Someone posts a track from an artist you've never heard. You check the label. The label has a dozen other artists you've also never heard. One Reddit post just opened a month of listening.
Rate Your Music is the other discovery tool worth knowing. Community-driven ratings with the most detailed genre taxonomy on the internet — you can filter charts by subgenre, year, country, and mood descriptors. Want the highest-rated ambient albums from Japan in the last three years? RYM will give you that list. No streaming algorithm comes close to that kind of specificity.
Album of the Year does something similar but focused on what's coming out now — it aggregates critic scores alongside user ratings, so you can see at a glance what's landing well this week without reading ten different review sites.
Bandcamp Daily publishes multiple times a day — album of the day picks, genre deep dives, artist features that skew toward independent and underground releases. It's editorial discovery, not algorithmic, and the quality has been consistent for years.
Shazam belongs here too, in a sideways kind of way. A hundred billion songs identified since launch, mostly used to name something you heard and forgot. But the discovery angle is underrated. Shazam a track at a club or from a DJ mix, then follow the thread: who produced it, what label put it out, what else is on that label. The identification is the spark. The digging is what happens after.
Community discovery takes effort. You have to show up, read threads, follow rabbit holes. The tradeoff is that recommendations from real people who share your taste will always be more interesting than what an algorithm generates from your listening data.
Labels
This is the approach most people skip, and it's where serious discovery lives.
If your taste is more scene-shaped than artist-shaped, labels are a cleaner signal than any playlist. Burial can go quiet for years. Hyperdub won't. Aphex Twin might not release anything for a long stretch. Warp still can. One good label is worth following fifty individual artists.
Spotify has a label: search operator — try label:hyperdub and you'll get a clean catalog view — but there's no way to get notified when something new shows up there. Bandcamp is better: follow a label and actually get updates in your feed. For scenes where Bandcamp is still a real home — ambient, small-run techno, underground electronic — it's the best label-following experience available. Bandcamp Fridays help too: eight times a year, the platform waives its revenue share and label pages light up with new releases and deep-catalog finds. Over $150 million has gone directly to artists and labels through those events since 2020.
Labels are also how you find new artists before anyone else catches on. When Shall Not Fade or Ilian Tape puts out something from a name you don't recognize, the label's track record is the reason you press play. Five labels you trust will surface more new music in a month than Discover Weekly will in a year.
Not sure where to start? Check the label field on five records you saved recently. If the same name keeps appearing, that's your signal.
Credits — the deepest way to find new music
Every track on Spotify has credits — producers, songwriters, engineers, featured artists. Most listeners never tap past the album cover. The ones who do start noticing patterns.
Dan Snaith played drums on Floating Points' Cascade last year. Floating Points remixed two tracks from Caribou's Suddenly a few years before that. Both have orbited the same London electronic scene as Four Tet for over a decade — shared NTS Radio shows, overlapping credits, the same club nights at Plastic People. None of those connections show up on an artist profile page. They're all in the credits.
That's how credit-based discovery works. You're not following profiles. You're following patterns — recurring names in the margins of records you already love. A producer who keeps appearing on tracks you save. An engineer whose records always hit with a certain weight. A songwriter who bridges genres you didn't know were connected.
The manual version is rewarding but fragile. Open a record, check credits, cross-reference on Discogs, make a note, hope you remember to check back next month. It holds for three or four names. It breaks at fifteen, because now you're not discovering music — you're maintaining a spreadsheet.
I built Tracknack to automate that part. It uses album credits from Spotify and Discogs to track producers, songwriters, engineers, and labels, then keeps a Spotify playlist updated with their new releases. The credit-based approach is the deepest way to discover music. It shouldn't require a weekly research ritual to maintain.
Pick the approach that matches how you listen
These aren't exclusive. Most serious listeners combine them.
Algorithms as the baseline — let them run, take what's good, expect nothing comprehensive. Communities when you want to explore actively. Labels when your taste follows scenes more than individuals. Credits when you want to go deeper than the name on the cover.
The people who always seem to find music before everyone else aren't doing anything mysterious. They just picked an approach that matches how they actually listen, and stuck with it.
Sources and notes
Checked on March 2, 2026.
- Spotify: Getting music on Release Radar — eligibility rules and update schedule
- Spotify Newsroom: Discover Weekly turns 10 — 56 million artist discoveries per week, genre controls
- Apple Newsroom: Shazam hits 100 billion — 100 billion song identifications since launch
- Bandcamp blog: Bandcamp Fridays return in 2026 — $150 million+ to artists since 2020
- RateYourMusic charts — genre, year, and descriptor filtering
- Album of the Year — aggregated critic and user scores for current releases
- Spotify support: Search — label: search operator
- Floating Points — Cascade on Discogs — Dan Snaith (Caribou) credited on drums
