Overview Leaderboard Methodology
Industry Report

Music Discovery Apps

Apps and services focused on surfacing new artists, tracks, and personalized discovery features like algorithmic playlists and tastemaker curation.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
Spotify
99/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Apple
100

Highest score on the LBA metric in this industry.

Authority Leader?
Spotify
100

Highest score on the Authority metric in this industry.

TOM Leader?
Spotify
100

Highest score on the TOM metric in this industry.

Spotify is the default answer in AI responses for Music Discovery Apps

When users ask ChatGPT, Claude, or Gemini about Music Discovery Apps, Spotify is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Apple is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 37 Music Discovery Apps brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Spotify
spotify.com
 96
100
100
99
2
Apple
apple.com
 100
63
89
83
3
SoundCloud
soundcloud.com
 84
55
71
69
4
Bandcamp
bandcamp.com
 79
58
56
64
5
YouTube TV
youtube.com
 84
38
80
64
6
Last.fm
last.fm
 77
30
42
46
7
Pandora
pandora.com
 77
15
62
43
8
TIDAL
tidal.com
 77
14
42
37
9
TikTok
tiktok.com
 94
9
9
22
10
Amazon
amazon.com
 89
9
9
21
11
Shazam
shazam.com
 89
9
9
21
12
Discogs
discogs.com
 83
8
8
20
13
Audiomack
audiomack.com
 75
8
9
19
14
Qobuz
qobuz.com
 77
8
8
19
15
Rate Your Music
rateyourmusic.com
 72
7
7
18
16
Deezer
deezer.com
 71
7
7
17
17
JioSaavn
jiosaavn.com
 71
7
7
17
18
TuneIn
tunein.com
 71
7
7
17
19
Anghami
anghami.com
 67
7
7
16
20
Gaana
gaana.com
 63
6
6
16
21
Hype Machine
hypem.com
 65
7
7
16
22
IDAGIO
idagio.com
 64
6
6
16
23
Mixcloud
mixcloud.com
 63
6
6
16
24
R
Resso
resso.com
 66
7
7
16
25
AccuRadio
accuradio.com
 58
6
6
15
26
Boomplay
boomplay.com
 59
6
6
15
27
Mubert
mubert.com
 62
6
6
15
28
M
MusicHarbor
musicharbor.app
 60
6
6
15
29
Radiooooo
radiooooo.com
 59
6
6
15
30
Reddit Ads
reddit.com
 59
6
6
15
31
Joox
joox.com
 58
6
6
14
32
KKBOX
kkbox.com
 58
6
6
14
33
Napster
napster.com
 52
5
5
13
34
Jango
jango.com
 46
5
5
12
35
NTS
nts.live
 49
5
5
12
36
TasteDive
tastedive.com
 43
4
4
11
37
Trebel
trebel.io
 35
3
3
9

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Music Discovery Apps prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 287 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →