TL;DR
LuxDirect analysed responses across five conversational AI platforms in April 2026: ChatGPT, Claude, Gemini, Grok, and Perplexity. Across 7,190 valid conversational AI responses from 15 Manchester independent luxury hotels, two properties captured 25.9% of all AI mentions. Eight of 15 properties had zero unprompted competitive visibility across all five conversational platforms. Manchester's AI visibility market remains less consolidated than London's. The window for independent properties to establish stronger AI visibility before the market consolidates remains open.
In April 2026, LuxDirect completed CS9-Manchester across five conversational AI platforms: ChatGPT, Claude, Gemini, Grok, and Perplexity. The study ran 2,475 structured prompts across five conversational AI platforms (ChatGPT, Claude, Gemini, Grok, and Perplexity), generating 7,190 valid responses after quality control. The study measures how AI systems surface, describe, and recommend hotels in conversational responses. Responses were scored only when a hotel was explicitly named or unambiguously referenced. Generic references such as "a luxury hotel in central Manchester" were excluded unless attributable to a specific property. Findings are based on structured query testing across five conversational AI platforms via API. This is the latest in LuxDirect's series of structured AI visibility studies of UK luxury hotel markets, following studies of London, Edinburgh and Cambridge.
Visibility is concentrated and the gap is structural
Across 7,190 valid conversational AI responses, platforms generated 1,525 hotel mentions. The distribution is not close to even. The top two properties captured 25.9% of all AI mentions between them. The top five captured 56.1%. The bottom five collectively held 13.7%. The concentration pattern replicates LuxDirect's London finding (57.2% top five share) and its Cambridge finding. Observed patterns across LuxDirect's London, Cambridge, and Manchester studies suggest visibility concentration increases as AI systems accumulate more reference material around frequently cited properties.
Full visibility rankings: all 15 properties
Hotel identities are anonymised. Full named reports are available to clients.
| Rank | Property | Type | Mentions | ASOV | Mention rate |
|---|---|---|---|---|---|
| 1 | Property A | Independent | 200 | 13.1% | 41.8% |
| 2 | Property B | Independent | 195 | 12.8% | 40.6% |
| 3 | Property C | Independent | 158 | 10.4% | 32.9% |
| 4 | Property D | Independent | 156 | 10.2% | 32.6% |
| 5 | Property E | Independent | 146 | 9.6% | 30.4% |
| 6 | Property F | Independent | 103 | 6.8% | 21.5% |
| 7 | Property G | Independent | 100 | 6.6% | 20.9% |
| 8 | Property H | Independent | 94 | 6.2% | 19.6% |
| 9 | Property I | Independent | 92 | 6.0% | 19.3% |
| 10 | Property J | Independent | 72 | 4.7% | 15.0% |
| 11 | Property K | Independent | 60 | 3.9% | 12.5% |
| 12 | Property L | Branded | 46 | 3.0% | 9.6% |
| 13 | Property M | Independent | 42 | 2.8% | 8.8% |
| 14 | Property N | Independent | 35 | 2.3% | 7.3% |
| 15 | Property O | Independent | 26 | 1.7% | 5.4% |
Top 5 ASOV share: 56.1% · Bottom 5 ASOV share: 13.7%
ASOV: AI Share of Voice, calculated as each property's total mentions as a proportion of all 1,525 hotel mentions recorded across the conversational platform study. Mention rate: percentage of conversational AI responses in which each property appeared across all query categories.
53% of properties have zero unprompted competitive visibility
When conversational AI platforms are asked about a specific property by name, the average hotel in the study appears in 77% of responses. When platforms are asked to recommend the best luxury hotels in Manchester without a named prompt, that figure falls to 9.6%. For 8 of 15 properties, the unprompted competitive mention rate is exactly zero across all five platforms.
AI knowledge of the property exists. AI advocacy does not.
This distinction matters commercially. A hotel that AI recognises but never recommends occupies a structurally weak position that product quality alone does not appear sufficient to correct.
Platform behaviour is divergent
Each conversational platform exhibits distinct recommendation patterns. The mean mention rate varies from 27.7% on Claude to 17.8% on ChatGPT. Several properties score near zero on one platform while maintaining measurable presence on others.
| Property | ChatGPT | Claude | Gemini | Grok | Perplexity | Total |
|---|---|---|---|---|---|---|
| Property A | 56% | 63% | 32% | 22% | 37% | 42% |
| Property B | 42% | 74% | 21% | 26% | 41% | 41% |
| Property C | 30% | 44% | 22% | 43% | 26% | 33% |
| Property D | 19% | 55% | 25% | 19% | 46% | 33% |
| Property E | 24% | 34% | 21% | 22% | 51% | 30% |
| Property K | 0% | 12% | 16% | 18% | 18% | 13% |
| Property L | 5% | 10% | 14% | 16% | 3% | 10% |
| Property N | 1% | 6% | 18% | 4% | 7% | 7% |
| Property O | 1% | 4% | 10% | 13% | 0% | 5% |
Selected properties shown. 0% means no mentions across the full study on that platform.
Property K registered 0% on ChatGPT while scoring 16% on Gemini and 18% on Grok. Property L registered 3% on Perplexity while scoring 16% on Grok. The platform a traveller opens determines whether a hotel exists in their consideration set at all. A hotel monitoring a single platform receives a fundamentally misleading picture of where it actually stands.
Booking intent is where visibility drops
For branded and discovery queries, conversational AI platforms mention properties readily. When a guest signals booking intent, mention rates fall sharply. Across booking intent queries, the average property was named in 32.5% of responses, meaning it went unmentioned in approximately 67.5%. Per-property mention rates on booking intent queries ranged from 20% to 44%. Even the strongest performers were absent from a majority of booking intent responses. This measures whether the property was named in the response text. It does not measure booking links, clicks, or where any reservation was completed.
| Property | Named on booking intent queries | Not named |
|---|---|---|
| Property A | 44.4% | 55.6% |
| Property E | 44.4% | 55.6% |
| Property D | 40.9% | 59.1% |
| Property B | 40.0% | 60.0% |
| Property C | 37.8% | 62.2% |
| Property F | 33.3% | 66.7% |
| Property G | 33.3% | 66.7% |
| Property H | 33.3% | 66.7% |
| Property I | 33.3% | 66.7% |
| Property J | 31.1% | 68.9% |
| Property M | 27.3% | 72.7% |
| Property K | 24.4% | 75.6% |
| Property L | 24.4% | 75.6% |
| Property N | 20.0% | 80.0% |
| Property O | 20.0% | 80.0% |
Summary
CS9-Manchester studied five conversational AI platforms across 15 Manchester independent luxury hotels, generating 7,190 valid responses. Two properties captured 25.9% of all conversational AI mentions. Eight of 15 properties had zero unprompted competitive visibility. Manchester's AI visibility market remains less consolidated than London's. Independent properties that address their AI signals now will be in a materially stronger position than those that engage reactively.
Frequently asked questions
How concentrated is AI hotel visibility in Manchester?
Significantly, though Manchester's AI visibility market remains less consolidated than London's (57.2% top five ASOV share) or Cambridge's (87% top four share within that study's sample). In the Manchester conversational platform study, the top five properties captured 56.1% of all AI mentions and the bottom five held 13.7%. Eight of 15 properties had zero unprompted competitive visibility across all five platforms, meaning AI never included them when asked to suggest the best luxury hotels in Manchester without a named prompt.
Why does platform divergence matter commercially?
The platform a traveller opens determines whether a hotel exists in their consideration set at all. In the Manchester study, one property registered 0% on ChatGPT while scoring 16% on Gemini and 18% on Grok. Another registered 3% on Perplexity while scoring 16% on Grok. A property monitoring a single platform receives a fundamentally misleading picture of where it actually stands. A hotel invisible on one platform but visible on others has a platform-specific gap that appears specifically addressable without a full content overhaul.
When does hotel visibility drop in AI interactions?
At the moment of booking intent. For branded and discovery queries, conversational AI platforms mention properties readily. When a guest signals transactional intent, the average property was named in only 32.5% of responses, going unmentioned in approximately 67.5% of booking intent queries.
What percentage of Manchester properties have zero competitive AI visibility?
53%. Eight of 15 properties had zero unprompted competitive visibility across all five conversational platforms. When AI is asked to recommend the best luxury hotels in Manchester, these properties do not appear in any response on any platform, regardless of product quality or guest satisfaction scores.
How does Manchester compare to London?
Although the top five concentration figures appear similar between Manchester (56.1%) and London (57.2%), London exhibits sharper long-tail collapse, with lower-tier properties appearing less consistently across platforms and query types. Manchester retains a broader mid-market visibility layer at this stage. Observed patterns across LuxDirect's studies suggest this layer compresses as AI training data accumulates around top-tier anchor properties. Independent properties that establish AI signals now are likely to hold a structural advantage as the market consolidates.
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