BrandInsightAI Insights
Travel · a live data story

Budget Hotels,
according to AI

Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about budget hotels — and record exactly which brands they put forward. Right now, Premier Inn owns the conversation.

0 AI answers this run · 0 brands named · measured, never estimated

The podium

Premier Inn is the default answer.

Named in 40% of budget hotels answers, typically in position 1.6. Travelodge follows at 37%, ibis at 25%.

Travelodge
37% of answers
Premier Inn
40% of answers
ibis
25% of answers
The full board

Every brand AI names, ranked.

Visibility is the share of answers naming the brand; citation share is its slice of all brand-owned pages cited; read→cited is how often its pages convert a read into a citation.

#BrandVisibilityAvg. positionCitation shareRead→cited
1Premier Inn 40% 1.6 48% 67%
2Travelodge 37% 1.8 43% 0%
3ibis 25% 3.9 9%
4Holiday Inn 12% 3.3 0%
5Holiday Inn Express 12% 4.3 0%
6easyHotel 10% 4.0 0%
7Point A Hotels 3% 6.5 0%
8Alhambra Hotel 2% 1.0 0%
9Crowne Plaza 2% 2.0 0%
10The Pilgrm 2% 2.0 0%
11Z Hotels 2% 3.0 0%
12Bloc Hotels 2% 4.0 0%
13Mercure 0% 0%
14Novotel 0% 0%
What AI wants here

Budget Hotels is decided on attraction.

Being named is visibility. Underneath it, every answer describes a brand in three ways — how much it stands out, how much it belongs, and how much it is returned to. In budget hotels, citizenM leads attraction at 145 against Premier Lodge at 69, indexed on the category at 100.

Attraction
citizenM145
Premier Lodge69
76-point spread · tracks being named -0.19
Affinity
citizenM120
Premier Lodge75
45-point spread · tracks being named -0.14
Attachment
Premier Inn123
Premier Lodge83
40-point spread · tracks being named 0.21
citizenM: Attraction 145, Affinity 120, Attachment 111
citizenM
Complete desire
YOTEL: Attraction 131, Affinity 104, Attachment 103
YOTEL
Magnetic but unbought
Alofts: Attraction 122, Affinity 106, Attachment 103
Alofts
Magnetic but unbought
AttractionAffinityAttachment

Each whorl lights one ring per index threshold cleared. See the full budget hotels desire edition →

Who AI trusts here

The referees of budget hotels.

The independent sources AI models cite when answering budget hotels questions — the places a brand needs to be seen, reviewed and ranked.

booking.com 10 cites
gov.uk 9 cites
reddit.com 6 cites
quora.com 5 cites
citizensadvice.org.uk 4 cites
facebook.com 4 cites
ricksteves.com 3 cites
ae-ca.co.uk 2 cites
mews.com 2 cites
perk.com 2 cites
Read is not cited

Premier Inn converts reads into citations.

When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Premier Inn converts 67% of reads. That gap is a content problem, not a visibility problem.

Premier Inn · read 3×67%
Full data table
#BrandVisibilityAvg. positionCitation shareRead→cited
1Premier Inn40%1.648%67%
2Travelodge37%1.843%0%
3ibis25%3.99%
4Holiday Inn12%3.30%
5Holiday Inn Express12%4.30%
6easyHotel10%4.00%
7Point A Hotels3%6.50%
8Alhambra Hotel2%1.00%
9Crowne Plaza2%2.00%
10The Pilgrm2%2.00%
11Z Hotels2%3.00%
12Bloc Hotels2%4.00%
13Mercure0%0%
14Novotel0%0%
Which AI you ask

The models do not agree on who leads.

Ask about budget hotels and the brand you are shown depends on the assistant: Claude → Premier Inn, Gemini → Premier Inn, ChatGPT → ibis. Their top-five lists share just 67% of names.

Claude recommends
Premier Inn
named in 35% of its answers
Gemini recommends
Premier Inn
named in 70% of its answers
ChatGPT recommends
ibis
named in 15% of its answers

Brands whose visibility swings most between models — the bar per model, widest gap on the right.

Premier Inn 55pp
Travelodge 50pp
ibis 20pp
easyHotel 20pp
ClaudeGeminiChatGPT
The data behind this chart
BrandClaudeGeminiChatGPTSpread
Premier Inn35%70%15%55pp
Travelodge30%65%15%50pp
ibis25%35%15%20pp
easyHotel0%20%10%20pp
Holiday Inn Express10%15%10%5pp
Holiday Inn10%15%10%5pp
Alhambra Hotel5%0%0%5pp
Crowne Plaza5%0%0%5pp
Point A Hotels5%0%5%5pp
The Pilgrm5%0%0%5pp
What AI reads here

Editorial carry budget hotels.

Every page AI opened while answering, classified by what kind of page it is. Editorial supply the most citations; faq convert best — 90% of the ones models opened were actually cited.

Editorial
25 cited · 10 read only
71% of reads cited
How-to guides
24 cited · 10 read only
71% of reads cited
Community threads
11 cited · 14 read only
44% of reads cited
faq
9 cited · 1 read only
90% of reads cited
Product pages
9 cited · 4 read only
69% of reads cited
Listicles
8 cited · 8 read only
50% of reads cited
Other
5 cited · 17 read only
23% of reads cited
Documentation
3 cited · 15 read only
17% of reads cited
The data behind this chart
Page typeCitedRead but not citedConversion
Editorial251071%
How-to guides241071%
Community threads111444%
faq9190%
Product pages9469%
Listicles8850%
Other51723%
Documentation31517%
What gets cited

Answer up front is what separates cited from ignored.

Of the budget hotels pages models actually opened, how much more often each feature's pages ended up in the cited sources. Answer up front is worth 15 percentage points; hard statistics pages fare 27pp worse. Measured within the read population, so selection can't flatter it.

Answer up front +15pp
Updated this year +11pp
Comparison table +6pp
Named author -5pp
Hard statistics -27pp
The data behind this chart
FeaturePages withCited %Pages withoutCited %Difference
Answer up front9663%9347%+15pp
Updated this year4464%14552%+11pp
Comparison table2560%16454%+6pp
Named author6652%12357%-5pp
Hard statistics4434%14561%-27pp
Citation readiness

Travelodge builds pages AI can quote.

Readiness scores each brand's own pages on the structure models reward — a direct answer up front, tables, hard numbers, named authors, structured data, recency, specifications. Set against how often those pages are actually cited.

BrandReadinessPages citedPages profiled
Travelodge 17 50% 6
Premier Inn 9 72% 18

Readiness is the share of eight measurable structural signals present on a brand's profiled pages. It is a build-quality measure, not a ranking of the brand.

Keep exploring

Nineteen more categories.

Method: 20 unbranded consumer prompts per category, spread across the buying journey, run weekly against ChatGPT, Claude and Gemini. Read→cited uses Claude and ChatGPT only (Gemini does not separate the two). Correlational observations of model behaviour at the time of the run. Data from the run completed Wed, 02 Sep 2026 05:02:34 GMT.

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