Overview Leaderboard Methodology
Industry Report

Designer Colognes & Men’s Fragrances

Fragrances specifically marketed toward men from well-known designer brands and fragrance houses.

Brands tracked: 31
Brands analyzed: 31
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 247
Total responses: 1,252
Top Brand Overall?
Dior
87/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Prada
99

Highest score on the LBA metric.

Authority Leader?
Dior
77

Highest score on the Authority metric.

TOM Leader?
Dior
100

Highest score on the TOM metric.

Dior is the default answer in AI responses for Designer Colognes & Men’s Fragrances

Dior and Chanel together dominate AI responses for Designer Colognes & Men’s Fragrances. 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 31 Designer Colognes & Men’s Fragrances 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
Dior
dior.com
 86
77
100
87
2
Chanel
chanel.com
 88
60
90
78
3
Versace
versace.com
 95
21
71
52
4
Tom Ford
tomford.com
 89
13
62
42
5
Prada
prada.com
 99
18
39
41
6
Creed
creedboutique.com
 83
13
51
38
7
Yves Saint Laurent
yslbeauty.com
 94
11
35
33
8
Hermès
hermes.com
 90
8
34
30
9
Acqua di Parma
acquadiparma.com
 86
16
17
28
10
Montblanc
montblanc.com
 79
9
10
19
11
Calvin Klein
calvinklein.com
 82
3
14
15
12
Azzaro
azzaro.com
 76
4
9
14
13
Maison Francis Kurkdjian
maisonfranciskurkdjian.com
 87
3
8
13
14
Parfums de Marly
parfums-de-marly.com
 76
4
6
12
15
Jean Paul Gaultier
jeanpaulgaultier.com
 96
0
28
3
16
Rabanne
rabanne.com
 83
0
37
3
17
Amouage
amouage.com
 87
0
4
2
18
Carolina Herrera
carolinaherrera.com
 86
0
6
2
19
Hugo Boss
hugoboss.com
 88
0
5
2
20
Burberry
burberry.com
 83
0
0
1
21
Givenchy
givenchy.com
 85
0
2
1
22
Guerlain
guerlain.com
 88
0
3
1
23
M
Mancera
parfumsmancera.com
 74
0
2
1
24
Davidoff
zinodavidoff.com
 85
0
0
0
25
Dolce&Gabbana
dolcegabbana.com
 92
0
0
0
26
Emporio Armani
armani.com
 91
0
0
0
27
Initio Parfums Privés
initio-parfums.com
 75
0
0
0
28
Issey Miyake
isseymiyake.com
 92
0
0
0
29
K
Kilian Paris
kilianparis.com
 80
0
0
0
30
Penhaligon's
penhaligons.com
 81
0
0
0
31
Viktor&Rolf
viktor-rolf.com
 90
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 247 shared Designer Colognes & Men’s Fragrances 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 247 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 →