What Is GEO? A Hotel Marketer's Guide to Generative Engine Optimisation
GEO helps hotels get recommended by ChatGPT, Gemini and Perplexity. AI-referred traffic grew 527% in 2025. Learn the 5 signals that drive citations.
Generative Engine Optimisation (GEO) is the practice of making your hotel visible to AI-powered search platforms: ChatGPT, Google Gemini, Perplexity, and Claude. Where traditional SEO targets search engine rankings, GEO targets the recommendation lists those AI systems generate when a traveller asks, “What’s the best design hotel in Berlin Mitte?”
That question used to produce a list of blue links. Now it produces a curated answer with three to five named hotels. If yours isn’t one of them, you’ve been passed over before the traveller even opens a booking site.
TL;DR: GEO is the discipline of making your hotel recommendable by AI. ChatGPT now has 900 million weekly active users (OpenAI, 2025), and AI-referred web sessions grew 527% between January and May 2025 (SparkToro, 2025). Hotels that don’t optimise for AI recommendation are already losing bookings to competitors who do.
Why Does GEO Matter for Hotels Right Now?
AI-referred web traffic grew 527% between January and May 2025 (SparkToro, 2025). That is not a forecast; it is a figure already on the books. ChatGPT alone reaches 900 million weekly active users (OpenAI, 2025), and Google AI Overviews now reaches 1.5 billion users every month across 200 countries (Google, 2025).
The shift in traveller behaviour is structural, not cyclical. More than 50% of Google searches now trigger an AI Overview rather than a traditional results page (industry data, 2025). Gartner forecasts that traditional search engine volume will fall 25% by 2026. Hotels built their digital marketing strategies around ranking on page one of Google. That page looks fundamentally different today, and it will look different again in twelve months.
In our experience auditing hotel group websites across Europe and the Asia-Pacific, fewer than one in five properties appear in AI recommendation responses for their own target queries. The hotels that do appear share a consistent set of technical and content signals that we can measure, compare, and improve.
The question is no longer whether AI search matters for hotel marketing. It’s whether your properties are visible when travellers use it.
How Does GEO Differ From Traditional SEO?
Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query (Ahrefs, 2025). That single figure is the clearest answer to how GEO differs from SEO: ranking well on Google does not reliably make you visible on AI platforms. The two systems reward different signals, and a strategy built only for one will underperform on the other.
GEO and SEO share the same foundation: quality content, credible sources, and a well-structured website. The difference lies in what each system rewards at the point of selection. SEO selects pages based on relevance, authority, and technical compliance. AI systems select properties based on confidence: can the model generate a credible, specific recommendation with enough supporting evidence?
That distinction changes the tactics. Here’s how the two disciplines compare:
| Dimension | Traditional SEO | GEO |
|---|---|---|
| Primary goal | Rank a page in search results | Get recommended in an AI response |
| Key signal | Backlinks and on-page relevance | Structured data, review volume, content depth |
| Unit of optimisation | Individual web pages | The property as an entity |
| Result format | A ranked list of links | A curated recommendation with description |
| Feedback loop | Google Search Console | Direct query testing across AI platforms |
| Update frequency | Algorithm updates (months) | Model training cycles (faster, less predictable) |
| Content style | Keyword-targeted copy | Conversational, queryable, factual content |
The most counterintuitive implication of that 11% figure: hotels that have invested years building domain authority for Google are starting from scratch on the AI platforms their guests use most. Their backlink profile carries almost no weight in ChatGPT or Perplexity’s selection logic. The disciplines overlap but they don’t transfer.
A strong SEO programme is still necessary. It’s no longer sufficient.
→ Related: How does GEO differ from traditional hotel SEO?
How Do AI Systems Decide Which Hotels to Recommend?
AI recommendation is not a black box, though it is often treated as one. Research into citation patterns reveals that brand mentions correlate 3 times more strongly with AI citations than backlinks do (Ahrefs, December 2025). That single finding overturns a decade of hotel SEO orthodoxy and points directly to what GEO requires: build the property’s reputation as a named entity across the sources AI systems index.
There are five measurable signals that determine whether an AI platform recommends your hotel.
Signal 1: Structured Data
Schema markup is machine-readable metadata embedded in your website’s HTML. When a page carries correct Hotel or LodgingBusiness schema, AI crawlers can extract facts about the property without interpreting prose. Name, address, star rating, price range, amenities, check-in time: all extractable directly from schema.
Most hotel websites have weak or absent schema markup. This is the highest-impact technical gap we find in audits, and it’s almost always fixable without a full website rebuild.
Signal 2: Review Health
Review volume, recency, and average rating across TripAdvisor, Booking.com, and Google Business Profile are among the most reliable signals an AI can use to assess a property’s quality. A hotel with 2,400 reviews averaging 4.6 on TripAdvisor is easier to recommend with confidence than one with 180 reviews at 4.1.
Recency matters particularly. Reviews from the past 90 days signal that the property is actively operating and that current guests endorse it.
Signal 3: Content Depth
AI systems are reading your website. A property page with 150 words of marketing copy cannot answer the specific conversational queries travellers bring to AI: “Is there parking?” “How far is it from the airport?” “Is it suitable for a honeymoon?” Pages that answer these questions in plain, factual prose are meaningfully more likely to be cited.
The threshold in our scoring model is 1,000 words of descriptive content per property page, with explicit FAQ content, neighbourhood guidance, and transport information included.
Signal 4: Digital Footprint
AI models weight editorial sources: travel journalism, independent blog coverage, YouTube video reviews, Reddit discussions, and Wikipedia mentions. Instagram and TikTok are largely invisible to current AI systems. A property that has earned coverage in third-party editorial sources accumulates a trust signal that no amount of on-site content can fully replicate.
Signal 5: LLM Visibility Score
This is the direct measure: run the actual queries your target travellers use and record whether your property is mentioned, at what position, and how it’s described. 92% of AI Overview citations come from pages that rank in the top ten of Google, but 47% of those come from pages ranking below position five (Ahrefs, 2025). That gap shows the AI systems are applying additional selection criteria beyond organic rank.
→ See how Waymarker scores these five dimensions.
Does Each AI Platform Work Differently?
Yes, and the differences are substantial enough to change your strategy. Only 11% of domains earn citations from both ChatGPT and Google AI Overviews for the same query (Ahrefs, 2025), which confirms that each platform operates distinct selection logic. Understanding how they differ tells you where to invest effort for each channel.
Each platform has its own data sources, weighting, and recommendation behaviour. Here’s what hotel marketers need to know about each.
ChatGPT
OpenAI’s model (particularly the GPT-4o family with web browsing enabled) draws heavily on indexed web content and editorial sources. It tends to favour properties with strong narrative presence: detailed property descriptions, press coverage, and prominent third-party mentions. Its citation behaviour is less transparent than Perplexity’s, but structured data and review volume both influence output quality.
Google Gemini
Gemini has native access to Google’s index, including Google Business Profile data, Google Maps reviews, and YouTube content. For hotel visibility on Gemini, maintaining a complete and active Google Business Profile is non-negotiable. Review recency on Google carries disproportionate weight here compared to the other platforms.
Perplexity
Perplexity is the most citation-transparent of the four platforms. It shows its sources, which means you can directly audit which pages it draws on to construct a recommendation. TripAdvisor, Booking.com, and travel media publications feature prominently. Perplexity’s real-time web access means it reflects current review scores more quickly than models with longer training cycles.
Claude (Anthropic)
Claude’s web-browsing capability is more selective than Perplexity’s. It tends to weight authoritative travel media and structured factual claims. Properties with well-organised schema markup and clear, unambiguous factual content tend to surface more consistently.
Because only 11% of domains earn citations from both ChatGPT and Google AI Overviews for the same query (Ahrefs, 2025), a hotel cannot assume that doing well on one platform means it performs well across all four. Monitoring must cover all platforms to identify where gaps exist and where investment will have the most impact.
→ See Waymarker’s monthly monitoring plans.
What Should Hotel Marketers Do First?
Brand mentions correlate 3 times more strongly with AI citations than backlinks do (Ahrefs, December 2025), yet most hotel marketing budgets are still weighted heavily towards link-building. The implication is clear: the highest-return actions for AI visibility are different from the highest-return actions for traditional SEO, and the order in which you tackle them matters.
The five signals above can feel overwhelming simultaneously. In practice, there’s a clear sequence.
Establish a baseline. You can’t prioritise fixes without knowing where you actually stand. This means running the queries your target travellers use — across all four platforms — and recording whether each property is mentioned, at what position, and who is appearing instead. It also means assessing your structured data, content depth, review health, and digital footprint against benchmarks from comparable properties. Without this baseline, investment in any individual fix is guesswork.
Fix structured data first. It’s consistently the lowest-scoring dimension in first audits and the fastest to move. Schema markup changes tend to show impact within a single monitoring cycle.
Expand content depth. Property pages need to answer the conversational queries AI systems are asked. This means going well beyond marketing copy: neighbourhood guidance, transport connections, dining detail, FAQ content, and accessibility information.
Build review recency. No GEO programme can compensate for a weak or stale review profile. A consistent post-stay review cadence across TripAdvisor, Google, and Booking.com is foundational.
Monitor continuously. AI models update. Competitors act. Platforms evolve. Visibility that looks strong today can erode within a quarter without a regular testing cadence across all four platforms.
The difficulty isn’t knowing these five things need to happen. It’s knowing exactly where each of your properties currently sits — and which fixes will have the most impact given your specific gaps and competitive set.
→ See what a Waymarker audit covers.
Frequently Asked Questions
Is GEO the same as AEO (Answer Engine Optimisation)?
GEO and AEO describe overlapping practices. AEO typically refers to optimising content to appear in featured snippets and direct answer boxes. GEO is broader: it covers the full range of AI-generated recommendation outputs, including conversational responses, curated lists, and comparison answers. For hotel marketing purposes, GEO is the more useful frame because it includes recommendation visibility, not just factual answer extraction.
Do I need a separate GEO strategy if my SEO is already strong?
A strong SEO programme provides a useful foundation, but it doesn’t transfer automatically. Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query (Ahrefs, 2025). Hotels with excellent Google rankings can still be invisible on ChatGPT or Perplexity. GEO requires targeted effort beyond traditional SEO, particularly in structured data and editorial footprint.
How quickly can a hotel improve its AI visibility?
Technical fixes — schema markup, structured data, content expansion — can produce measurable improvement within one to two AI model update cycles, typically one to three months. Review volume improvements take longer because they depend on guest behaviour over time. We generally advise clients to measure baseline visibility, implement technical fixes in the first month, and reassess at the three-month mark.
Which AI platform should hotels prioritise?
We recommend monitoring and optimising for all four platforms simultaneously because their selection logic differs enough that strong performance on one does not predict strong performance on others. If forced to prioritise, Perplexity is the most useful for rapid iteration because it shows citations directly. Gemini is highest priority for any property that relies on Google Business Profile as a core channel.
Does social media presence help with AI visibility?
Minimally, with the current generation of AI systems. Instagram and TikTok content is largely invisible to the AI platforms that matter for hotel recommendation. YouTube is the exception: video content about a property can surface in Gemini (which indexes YouTube natively) and in some Perplexity responses. Editorial blog content, TripAdvisor listings, and structured web content carry far greater weight than social media posts.
What’s the difference between a one-time GEO audit and ongoing monitoring?
A GEO audit establishes your baseline across all five visibility dimensions and produces a prioritised list of improvements. It’s a point-in-time snapshot. Ongoing monitoring tracks whether those improvements are working, catches competitor movements, and flags when visibility drops before it affects bookings. The audit is the starting point; monitoring is what protects and grows the gains.
→ Compare audit and monitoring tiers.
The Bottom Line
AI search isn’t coming; it’s here. The 527% growth in AI-referred web traffic recorded between January and May 2025 (SparkToro, 2025) represents a structural change in how travellers discover hotels, not a temporary experiment. The platforms driving that traffic, ChatGPT, Gemini, Perplexity, and Claude, use selection logic that rewards structured data, review credibility, content depth, and editorial presence.
Hotel marketing teams that understand those signals, measure their current performance against them, and implement improvements systematically will be recommended to travellers who never open a search engine. Those that don’t will keep paying for visibility they used to earn.
The good news: the competitive field is still wide open. Most hotels have done nothing. Getting in early means the comparison set is weak, and the gains compound as review volume and editorial coverage grow over time.