Overview Leaderboard Methodology
Industry Report

Running Shoes

Athletic footwear brands for road, trail, and race-day running.

Brands tracked: 30
Brands analyzed: 30
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 245
Total responses: 1,225
Top Brand Overall?
Brooks
89/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Nike
100

Highest score on the LBA metric in this industry.

Authority Leader?
Brooks
89

Highest score on the Authority metric in this industry.

TOM Leader?
Nike
96

Highest score on the TOM metric in this industry.

Brooks is the default answer in AI responses for Running Shoes

Brooks and ASICS together dominate AI responses for Running Shoes. 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 30 Running Shoes 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
Brooks
brooksrunning.com
 86
89
91
89
2
ASICS
asics.com
 88
85
90
87
3
Nike
nike.com
 100
48
96
77
4
HOKA
hoka.com
 87
44
89
70
5
Saucony
saucony.com
 83
49
84
70
6
New Balance
newbalance.com
 95
46
72
68
7
adidas
adidas.com
 93
13
57
43
8
Mizuno
mizuno.com
 89
9
36
33
9
On
on.com
 76
8
34
29
10
Altra
altrarunning.com
 75
8
17
23
11
PUMA
puma.com
 76
8
17
23
12
Salomon
salomon.com
 80
8
15
23
13
La Sportiva
lasportiva.com
 80
8
10
20
14
Skechers
skechers.com
 81
8
8
20
15
inov-8
inov8.com
 77
8
8
19
16
Merrell
merrell.com
 78
8
8
19
17
Topo Athletic
topoathletic.com
 74
7
7
18
18
Under Armour
underarmour.com
 72
7
7
18
19
norda
norda.com
 68
7
7
17
20
Li-Ning
lining.com
 65
6
6
16
21
Diadora
diadora.com
 61
6
6
15
22
Karhu
karhu.com
 59
6
6
15
23
Tracksmith
tracksmith.com
 60
6
6
15
24
Newton Running
newtonrunning.com
 58
6
6
14
25
NNormal
nnormal.com
 58
6
6
14
26
X
Xtep
xtep.com
 57
6
6
14
27
Craft
craft.do
 53
5
5
13
28
Speedland
runspeedland.com
 50
5
5
13
29
361°
361usa.com
 49
5
5
12
30
Joe Nimble
joenimble.com
 47
5
5
12

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 245 shared Running Shoes 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 245 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 →