Overview Leaderboard Methodology
Industry Report

Global Hotel Chains

Large multinational hotel brands operating hundreds to thousands of properties worldwide, offering standardized services and loyalty programs.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
Hilton
77/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Four Seasons
100

Highest score on the LBA metric.

Authority Leader?
Hilton
77

Highest score on the Authority metric.

TOM Leader?
Hilton
64

Highest score on the TOM metric.

Hilton leads the Global Hotel Chains category in AI responses

Hilton is the most consistently-surfaced brand when users ask AI assistants about Global Hotel Chains, but not to the point of monopolising the conversation. Hyatt and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 33 Global Hotel Chains 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
Hilton
hilton.com
 94
77
64
77
2
Hyatt
hyatt.com
 86
65
58
69
3
Accor
accor.com
 76
15
30
33
4
Wyndham
wyndhamhotels.com
 71
17
32
33
5
ibis
ibis.com
 78
17
13
26
6
Holiday Inn
holidayinn.com
 84
5
31
24
7
Holiday Inn Express
ihg.com
 84
5
18
20
8
Four Seasons
fourseasons.com
 100
3
27
19
9
InterContinental
intercontinental.com
 85
3
22
17
10
Westin
westin.com
 84
3
14
16
11
Sheraton
sheraton.com
 77
3
15
14
12
Motel 6
motel6.com
 63
5
4
11
13
Crowne Plaza
crowneplaza.com
 73
2
8
10
14
Novotel
novotel.com
 79
1
11
10
15
Best Western
bestwestern.com
 75
1
9
7
16
Pullman
pullmanhotels.com
 68
0
10
5
17
Mandarin Oriental
mandarinoriental.com
 93
0
18
3
18
B&B Hotels
hotel-bb.com
 67
0
9
2
19
Marriott Hotels
marriott.com
 86
0
5
2
20
Premier Inn
premierinn.com
 79
0
9
2
21
Shangri-La
shangri-la.com
 82
0
8
2
22
The Ritz-Carlton
ritzcarlton.com
 98
0
6
2
23
Meliá Hotels & Resorts
melia.com
 67
0
1
1
24
OYO
oyorooms.com
 69
0
1
1
25
Ramada
ramada.com
 74
0
3
1
26
Jumeirah
jumeirah.com
 82
0
0
0
27
Kempinski
kempinski.com
 71
0
0
0
28
Kimpton Hotels & Restaurants
kimptonhotels.com
 83
0
0
0
29
NH Hotels
nh-hotels.com
 66
0
0
0
30
Radisson Hotels
radissonhotels.com
 75
0
0
0
31
Scandic
scandichotels.com
 64
0
0
0
32
St. Regis Hotels & Resorts
stregis.com
 92
0
0
0
33
Taj Hotels
tajhotels.com
 84
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Global Hotel Chains 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 →