Overview Leaderboard Methodology
Industry Report

Subscription Learning Platforms

On-demand platforms that provide unlimited access to curated course libraries and learning paths for a recurring fee.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
Coursera
93/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Khan Academy
97

Highest score on the LBA metric.

Authority Leader?
Coursera
90

Highest score on the Authority metric.

TOM Leader?
Coursera
100

Highest score on the TOM metric.

Coursera is the default answer in AI responses for Subscription Learning Platforms

When users ask ChatGPT, Claude, or Gemini about Subscription Learning Platforms, Coursera is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. LinkedIn Learning 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 33 Subscription Learning Platforms brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Coursera
coursera.org
 88
90
100
93
2
LinkedIn Learning
linkedin.com
 88
64
100
83
3
Udemy
udemy.com
 73
35
85
60
4
Pluralsight
pluralsight.com
 84
29
80
58
5
Skillshare
skillshare.com
 79
27
73
54
6
MasterClass
masterclass.com
 75
24
70
50
7
DataCamp
datacamp.com
 86
9
56
35
8
Khan Academy
khanacademy.org
 97
16
20
32
9
Codecademy
codecademy.com
 80
5
35
25
10
edX
edx.org
 82
10
19
25
11
Rosetta Stone
rosettastone.com
 83
1
5
7
12
Brilliant
brilliant.org
 71
0
14
2
13
Domestika
domestika.org
 69
0
6
2
14
Skillsoft
skillsoft.com
 71
0
8
2
15
Wondrium
wondrium.com
 68
0
10
2
16
FutureLearn
futurelearn.com
 64
0
1
1
17
Treehouse
teamtreehouse.com
 69
0
1
1
18
Udacity
udacity.com
 73
0
1
1
19
365 Data Science
365datascience.com
 58
0
0
0
20
BBC Maestro
bbcmaestro.com
 60
0
0
0
21
Craftsy
craftsy.com
 65
0
0
0
22
Creativebug
creativebug.com
 71
0
0
0
23
CreativeLive
creativelive.com
 69
0
0
0
24
CXL
cxl.com
 76
0
0
0
25
Educative
educative.io
 74
0
0
0
26
Eduonix
eduonix.com
 26
0
0
0
27
iHASCO
ihasco.co.uk
 40
0
0
0
28
Kinnu
kinnu.xyz
 34
0
0
0
29
Laracasts
laracasts.com
 92
0
0
0
30
Mindvalley
mindvalley.com
 79
0
0
0
31
Noble Desktop
nobledesktop.com
 61
0
0
0
32
O'Reilly
oreilly.com
 83
0
0
0
33
OpenClassrooms
openclassrooms.com
 72
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Subscription Learning Platforms 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 263 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 →