ChatGPT vs Perplexity vs Gemini: Which Matters Most for Hospitality?

Not all AI engines are created equal

When Delphium Labs tested 300 hospitality queries across ChatGPT, Perplexity, and Gemini, each engine showed distinct patterns in how it discovers, evaluates, and recommends businesses. The differences are significant enough that optimising for one engine does not automatically improve your visibility on the others.

This matters because hospitality businesses have limited time and resources. Knowing where to focus, which engine to prioritise, and what specific actions drive visibility on each platform is the difference between an effective strategy and a wasted one.

We ran 300 queries spanning hotels, restaurants, pubs, wedding venues, and experience providers across the UK. Each query was tested on all three engines within the same 48-hour window in February 2026. We recorded which businesses were recommended, the sources cited, the format of the response, and the type of information each engine prioritised. Here is what we found.

ChatGPT: the largest audience, the hardest to crack

How it works

ChatGPT has the largest user base for travel and dining queries among the three AI engines. OpenAI reported over 300 million weekly active users in late 2025, and travel consistently ranks among the top query categories. When someone asks ChatGPT for a hotel recommendation, they are engaging with a model trained on a vast corpus of web data, supplemented by real-time Bing search results for current information.

What Delphium Labs found

In our 300-query test, ChatGPT showed the strongest preference for well-known brands and properties with high review volume. Chain hotels and established restaurant groups appeared in 76% of ChatGPT's hospitality recommendations. Independent properties appeared in 24%.

ChatGPT handles complex, conversational queries well. A question like "I need a hotel in London near the theatre district, dog-friendly, under 200 per night" produces a nuanced response with specific recommendations. The engine is strong at combining multiple criteria and returning relevant results. This is where ChatGPT excels relative to the other engines.

However, ChatGPT has notable weaknesses. It can hallucinate details, sometimes confidently stating incorrect information about room rates, amenities, or availability. In our testing, approximately 8% of ChatGPT's specific factual claims about individual properties were inaccurate. More concerning for newer or recently changed businesses, ChatGPT occasionally recommends properties that have closed or rebranded, drawing from outdated training data rather than current web information.

What drives ChatGPT visibility

Our analysis identified three primary factors that correlate with appearing in ChatGPT recommendations:

Broad web presence. ChatGPT favours businesses that are mentioned across many different websites. Properties featured in travel publications, food blogs, industry lists, and local guides perform significantly better than those with a strong website but limited third-party presence. The breadth of your web footprint matters more than the depth of any single page.

Review volume. Consistent with our earlier research, review volume is a stronger signal than review score for ChatGPT. Properties with 500-plus reviews across major platforms appeared at substantially higher rates than equally-rated properties with fewer than 100 reviews. The volume of text associated with your business in reviews gives ChatGPT more material to draw from.

Brand mentions across many sites. ChatGPT weighs how often and how consistently a business is mentioned by name across the web. Properties that appear in curated lists, "best of" articles, and editorial features have a measurable advantage. This is why PR and content marketing have outsized importance for ChatGPT visibility specifically.

Perplexity: the independent's best opportunity

How it works

Perplexity has a smaller but rapidly growing and highly engaged user base. Unlike ChatGPT, Perplexity performs real-time web searches for every query and explicitly cites its sources in every response. When Perplexity recommends a hotel, it tells the user exactly where that recommendation came from, whether it is a travel blog, a newspaper review, the hotel's own website, or a booking platform.

What Delphium Labs found

Perplexity was the most favourable engine for independent hospitality businesses in our testing. Independents appeared in 38% of Perplexity recommendations, compared to 24% on ChatGPT and 29% on Gemini. This difference is driven by Perplexity's reliance on live web search rather than trained knowledge.

Perplexity tends to surface niche content and recent articles. A boutique hotel that published a detailed blog post about its spring menu last week has a genuine chance of appearing in Perplexity results this week. That recency advantage does not exist on ChatGPT, where trained knowledge may be months old.

The weakness of Perplexity is inconsistency. Because it searches the live web for each query, results can vary significantly between similar queries asked on different days. Delphium Labs found that the same query asked three days apart produced meaningfully different recommendations in 31% of cases. The smaller audience also means that the absolute volume of discovery through Perplexity is lower than through ChatGPT or Gemini, though it is growing quickly.

What drives Perplexity visibility

Recent, specific web content. This is the dominant factor. Perplexity searches the current web, and it favours content that is recent, detailed, and specific. A blog post published this month about "what to eat in York" that mentions your restaurant will directly improve your chances of appearing in Perplexity responses about dining in York.

Blog posts and editorial coverage. Perplexity heavily cites articles from food and travel writers, local publications, and blog content. Properties that invest in content marketing or that generate regular press coverage see measurable results on Perplexity.

PR and food/travel articles. Being mentioned in a recent article by a food critic, a travel journalist, or a regional lifestyle publication carries significant weight. Perplexity explicitly cites these sources, and users see where the recommendation originated, which adds credibility.

Detailed website content. Your own website content matters on Perplexity, particularly pages with specific, useful information. Perplexity frequently cites property websites directly when they contain detailed descriptions, local guides, or specific factual content that answers the user's query.

Gemini: the Google ecosystem powerhouse

How it works

Gemini powers Google's AI Overviews and is deeply integrated into the Google ecosystem. When a user asks a travel or dining question through Google Search, the AI Overview that appears at the top of results is generated by Gemini. It draws heavily from Google Business Profile data, Google Maps, Google Reviews, and structured data indexed from the web.

What Delphium Labs found

Gemini showed the strongest local bias of the three engines. Its recommendations are heavily weighted toward Google's own data ecosystem. In our testing, Google Business Profile completeness was the single strongest predictor of whether a business appeared in Gemini-generated recommendations.

Gemini's strength for hospitality businesses is its massive distribution. AI Overviews now appear in an estimated 40% of travel-related Google searches in the UK. For sheer reach, no other AI engine comes close. If your business appears in a Gemini-generated AI Overview, it is being seen by a substantially larger audience than on either ChatGPT or Perplexity.

The weakness of Gemini is that it is less conversational and more factual and list-oriented than the other engines. Gemini tends to present structured information: name, rating, price range, location, key features. It is less likely to craft a narrative recommendation explaining why a particular property is a good fit for a specific type of traveller. For businesses whose appeal lies in atmosphere, personality, or unique character, Gemini's format can flatten the qualities that make them distinctive.

What drives Gemini visibility

Google Business Profile completeness. This is the dominant factor by a wide margin. Properties with fully completed GBP listings, including photos (50-plus), filled attribute fields, regular Google Posts, complete business descriptions, and up-to-date hours and contact information, appeared in Gemini responses at 2.3 times the rate of properties with minimal profiles.

Google Reviews volume and content. Gemini draws from Google Reviews far more heavily than from TripAdvisor or other review platforms. The volume of Google Reviews, the recency of reviews, and the specific content within reviews all influence whether and how Gemini recommends a business. Reviews that mention specific features ("amazing rooftop terrace", "best Sunday roast in Leeds") give Gemini material to match against user queries.

Structured data on your website. Schema markup is the second most important technical factor for Gemini visibility. Gemini processes structured data to understand property attributes, pricing, room types, menu items, and facilities. Properties with comprehensive schema were significantly more visible than those without.

Google Maps and local signals. Gemini integrates closely with Google Maps. Businesses with accurate, detailed Maps listings, including correct categories, complete address information, and associated photos, perform better. The local dimension is stronger on Gemini than on the other engines.

Head-to-head comparison

| Factor | ChatGPT | Perplexity | Gemini | |---|---|---|---| | Primary data source | Trained web data + Bing search | Live web search with citations | Google ecosystem (GBP, Maps, Reviews) | | Key optimisation lever | Broad web presence, review volume | Recent content, PR coverage | Google Business Profile completeness | | Independent visibility | 24% of recommendations | 38% of recommendations | 29% of recommendations | | Audience size | Largest | Smallest (but growing fast) | Largest via Google Search | | Response style | Conversational, narrative | Source-cited, article-like | Factual, list-oriented | | Best for complex queries | Strong | Moderate | Moderate | | Update frequency | Periodic training + live search | Real-time | Near real-time via Google index | | Hallucination risk | Moderate (8% error rate in testing) | Low (source-cited) | Low (data-backed) | | Booking integration | Emerging (Expedia partnership) | Active (booking links in results) | Strong (Google Hotels integration) |

Which should you focus on?

All three engines matter, but priorities should differ based on your business type and your current digital strengths.

Hotels

Priority order: Gemini, then ChatGPT, then Perplexity.

For hotels, Gemini's massive distribution through Google Search makes it the highest-impact engine. The actions that improve Gemini visibility, primarily GBP optimisation and schema markup, also have positive spillover effects on the other engines. ChatGPT ranks second because of its audience size and the growing integration with Expedia for hotel bookings. Perplexity is valuable for boutique and independent hotels that invest in content marketing, but the smaller audience makes it a secondary priority for most properties.

Restaurants

Priority order: Gemini (dominant), then Perplexity, then ChatGPT.

Restaurant discovery is more locally driven than hotel search, which makes Gemini and its tight integration with Google Maps and GBP the clear priority. Perplexity ranks second for restaurants because food and dining content is well represented on the platform, and restaurant reviews, food blog mentions, and menu-related content all perform strongly. ChatGPT is relevant but less differentiated for restaurant recommendations.

Wedding and event venues

Priority order: Perplexity, then Gemini, then ChatGPT.

Venue discovery is often research-intensive and content-driven. Couples searching for wedding venues ask detailed, multi-criteria questions that benefit from Perplexity's content-surfacing approach. Venues with detailed website content covering capacity, menus, pricing structures, and local accommodation options perform well on Perplexity. Gemini matters for local discovery, but GBP categories for venues are less developed than for hotels and restaurants.

Tour operators and experience providers

Priority order: Perplexity, then ChatGPT, then Gemini.

Experience and activity providers benefit most from content-rich discovery. Perplexity's preference for recent, detailed content makes it the strongest platform for tours, activities, and experience providers. ChatGPT handles the complex, multi-criteria queries common in experience search. Gemini is less effective here because experience provider GBP categories and structured data are less mature.

The cross-engine strategy

While priorities differ, certain actions improve visibility across all three engines simultaneously. Delphium Labs recommends these as the foundation of any AI visibility strategy:

Comprehensive Google Business Profile. Benefits Gemini directly and improves your data availability for ChatGPT and Perplexity indirectly.

Schema markup on your website. Helps all three engines understand your business attributes and present accurate information.

Regular, detailed content on your website. Blog posts, local guides, seasonal updates. Perplexity picks these up quickly, ChatGPT incorporates them over time, and Gemini indexes them through Google.

Active review generation. More reviews, particularly on Google, improve your visibility across all engines. Responding to reviews adds additional content that AI engines process.

Third-party mentions and editorial coverage. Press coverage, blog features, and inclusion in curated lists improve ChatGPT visibility directly and boost Perplexity visibility when those articles are published.

The landscape shifts fast

At Delphium Labs, we monitor all three engines continuously because the landscape changes quickly. The relative importance of each engine, the data sources they rely on, and the types of queries they handle well are all evolving. What we have described here reflects the state of play in early 2026. Six months from now, the balance may be different.

The constant across all scenarios is that businesses with strong foundational digital presence, good content, proper structured data, active review profiles, and well-maintained Google Business Profiles are better positioned regardless of how the engines evolve.

FindingFin checks your visibility across all three engines simultaneously, showing you where you appear, where you are absent, and what specific factors are driving the results. Because the engines behave differently, a single visibility score is not enough. You need to understand your position on each platform to make informed decisions about where to invest your time and resources.

Delphium Labs will continue publishing engine-specific research as ChatGPT, Perplexity, and Gemini evolve their hospitality capabilities. The businesses that track these changes and adapt their strategies accordingly will maintain a measurable advantage in an increasingly AI-driven discovery landscape.