Overview Leaderboard Methodology
Industry Report

Design System Management

Tools that help teams create, maintain, version, and distribute shared design components, patterns, and tokens across products.

Brands tracked: 35
Brands analyzed: 35
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 275
Total responses: 1,400
Top Brand Overall?
Figma
87/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Storybook
91

Highest score on the LBA metric in this industry.

Authority Leader?
Figma
80

Highest score on the Authority metric in this industry.

TOM Leader?
Figma
100

Highest score on the TOM metric in this industry.

Figma is the default answer in AI responses for Design System Management

Figma and Storybook together dominate AI responses for Design System Management. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 35 Design System Management 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
Figma
figma.com
 83
80
100
87
2
Storybook
storybook.js.org
 91
59
89
78
3
zeroheight
zeroheight.com
 60
70
98
74
4
Supernova
supernova.io
 35
39
76
47
5
Tokens Studio
tokens.studio
 69
29
51
47
6
Knapsack
knapsack.cloud
 38
16
49
32
7
Chromatic
chromatic.com
 79
8
30
29
8
Atlassian
atlassian.com
 80
8
25
27
9
Frontify
frontify.com
 75
9
23
27
10
GitHub
github.com
 81
8
16
24
11
UXPin
uxpin.com
 75
8
20
24
12
Backlight
backlight.dev
 45
5
42
23
13
Notion
notion.so
 77
8
16
23
14
Chakra UI
chakra-ui.com
 87
9
9
21
15
MUI
mui.com
 83
8
8
20
16
Bit
bit.dev
 63
6
13
19
17
Sketch
sketch.com
 73
7
7
18
18
Tokens Studio for Figma
tokenstudio.com
 67
7
9
18
19
Zeplin
zeplin.io
 74
7
7
18
20
Plasmic
plasmic.app
 67
7
7
17
21
I
InVision
invisionwfm.com
 64
6
6
16
22
Penpot
penpot.app
 67
7
7
16
23
Specify
specifyapp.com
 40
4
19
16
24
Abstract
abstract.com
 62
6
6
15
25
Fractal
fractal.build
 52
5
5
13
26
Nx
nx.dev
 54
5
5
13
27
Pattern Lab
patternlab.io
 52
5
5
13
28
Modulz
modulz.app
 41
4
4
11
29
Lingo
lingoapp.com
 21
2
7
8
30
Docz
docz.site
 24
2
2
7
31
Ditto
dittowords.com
 23
2
2
6
32
Catalog
catalog.style
 18
2
2
5
33
Ladle
ladle.dev
 9
1
9
5
34
Interplay
interplayapp.com
 12
1
1
4
35
Histoire
histoire.dev
 5
1
1
2

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 275 shared Design System Management 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 275 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 →