Is Your Hotel Ready for GPT Engine Optimisation?

In the hospitality industry, we’ve long focused on SEO (Search Engine Optimisation) to climb Google rankings and capture bookings. But travel planning behaviour is ever evolving. Increasingly, travellers are turning to AI assistants like ChatGPT to plan trips, ask for hotel recommendations, and even book rooms. Bypassing the traditional search engine funnel. Some marketers have started calling this shift GEO (GPT Engine Optimisation) or LLMO (Large Language Model Optimisation). The idea is simple but game-changing: instead of optimising to impress Google’s algorithm, hotels will need to optimise for AI-driven recommendations to remain discoverable.

Generative AI (Gen AI) only went mainstream in late 2022, but its impact on travel planning has been swift. Major players are already jumping in. Where Expedia and Kayak were among the first travel companies to integrate ChatGPT into their planning tools. Kayak’s new AI assistant even lets users converse naturally and pulls real-time hotel rates into the chat, making them instantly bookable. Giving not only new ideas, but also actionable answers, significantly changing the funnel. As Kayak’s Chief Product Officer put it, “This is not just a chatbot. You can ask any travel question, and in a conversation, you get real-life rates that are also bookable”. Meanwhile, Google is rolling out its own generative AI in search results, offering detailed answers and trip summaries from conversational prompts rather than just ten blue links. All signs point to a future where travellers rely on AI-driven conversations as much as (or more than) web searches and social media.

10 Blue Links vs. One Confident Answer

For years, winning online meant ranking high on Google. Travellers would type a query (“best hotels in London”), scan the results, maybe view the second results page, and perhaps click through to your website if your SEO was on point. With GPT-based assistants, this is shifting. Instead of a list of ranked links, the user gets one answer or a short curated list. A conversational, confident recommendation tailored to their specific query. This allows potential guests to query something very specific that a traditional search may struggle with. For example; "What are the best 4-star, pet-friendly hotels in Amsterdam that overlook a canal?” . Gen AI, on the other hand, can digest that request in one go and produce a specific answer with a few recommended hotels, possibly even with real-time availability and prices included. The AI isn’t just quoting one website; it’s synthesizing information from across the web to deliver the answer.

This one-answer dynamic means the rules for ranking are different. Traditional SEO ranking factors like keywords and backlinks don’t directly translate to how an AI language model chooses what to say. Google’s index is built on crawling and linking structure; where ChatGPT-style models rely on training data and real-time retrieval. They look for patterns and “knowledge” in vast datasets, including written content and user-generated text. In essence, LLMs don’t crawl websites for SEO signals, rather they retrieve facts and phrases. One industry commentator quipped that we’re entering the age of “GPT Engine Optimisation”, where the goal is to persuade AI models to pick your hotel when they generate an answer. That means thinking about AI retrievability: ensuring your hotel is mentioned often and favourably across the sources an AI is trained on or has access to. PR may just become your best friend.

So, what sources do AI assistants draw from? It turns out they pull from a much broader pool than a typical search engine results page. Large Language Models will synthesize content from structured databases, travel guides, news articles, and tons of unstructured text. Think forum posts, Q&As, travel blogs, and especially reviews. In fact, AI may treat a detailed TripAdvisor review or a travel blog mention as more valuable than your polished homepage, because those sources are conversational, context-rich, and unique. The AI cares about the content of the conversation around your hotel: what people are saying, in what context, and how often. It’s less about having the perfect meta tags and more about having your hotel organically embedded in relevant discussions and write-ups across the web. One SEO expert insight puts it this way: brand mentions are becoming the new backlinks. LLMs notice when your hotel’s name keeps popping up alongside relevant travel terms, even if those mentions aren’t hyperlinked.

It's important to remember though, that LLMs like GPT-4 may sound fluent, but they don’t truly “understand” language at all. They’re glorified pattern-matchers. Instead of grasping meaning the way a person would, an LLM breaks everything you say into tokens (pieces of words) and uses sheer statistics to predict what comes next. It’s essentially an extremely advanced autocomplete. The model combs through its gigantic training data and calculates which word or phrase is most likely to follow, based on patterns it has seen before. There’s no actual comprehension or reasoning happening. In truth, the AI has no idea what “London” or “luxury hotel” really means in a human sense; it’s simply learned that those tokens often show up together in certain contexts. The impressive answers you get are a product of billions of statistical weights crunching probabilities, not a thinking mind. In fact, under the hood an LLM doesn’t deal with words at all. It converts them into numbers (vectors) during training, and plays with those numerical relationships. The upshot: an LLM’s “knowledge” is nothing more than math, mapping patterns from its training text, without any true understanding of concepts or intent.

So, what does this mean for GEO in hospitality? It means you can’t game an AI model the way marketers tried to game Google’s algorithm. There’s no secret ranking signal or logical reasoning you can exploit, just patterns to be learned. Optimising for GEO is therefore about feeding the right patterns to the model. In practice, that means surrounding your hotel’s name and content with the right context, phrases, and signals so the AI learns to associate your brand with the ideas you care about. Instead of keyword-stuffing or tweaking meta-tags for a search crawler, you’re focusing on contextual relevance: ensuring that whenever your brand is mentioned, it’s in genuinely informative, on-topic content that reinforces your expertise. Over time, those contextual associations become the data that the LLM trains on. In other words, you’re training the AI, not tricking it. The goal is to teach the model that your hotel brand belongs in the answer when a user asks about, say, “best luxury stays in London,” by consistently pairing your name with rich, relevant info on that topic. GEO is all about cultivating these authentic signals, building real authority and clear relevance, rather than chasing algorithmic loopholes. It’s a smarter, more honest play.

That is to say, that while GEO is a different game, we do still see that strong SEO practices feed directly into GEO. As one marketing agency observed, to be good in GEO/AIO, you NEED to be good in SEO. Why? Because a well-structured website, good domain authority, and healthy Google presence ensure that the AI has accurate, high-quality material to draw from when learning or retrieving information about your hotel. Think of SEO as the foundation and GEO as the next floor up. If your hotel isn’t even visible to Google, it’s probably invisible to ChatGPT. The difference is where that visibility needs to manifest.

Travel Planning Turns Conversational (Ready or Not)

You've probably seen it in the countless industry newsletters: travel planning is already moving to conversational AI. A wave of new tools and features is bringing trip planning into chat interfaces. Expedia recently launched a ChatGPT-powered trip planner in its app that lets users converse to get hotel, flight, and destination recommendations. Instead of manually using filters and scrolling through listings, a traveller can just describe what they want and let the AI do the searching and sorting. Kayak went a step further by launching Kayak.ai, an AI travel assistant that combines ChatGPT’s conversational skills with Kayak’s live search data. Their users can now say “I need a hotel in NYC with great pool views for a family of four” and get an immediate, bookable suggestion in the same chat. As the Kayak team describes it, they’re blending planning, inspiration and booking into a single conversation. Essentially acting like a digital travel agent that has infinite patience and an encyclopaedic memory.

The shift to GPT's and LLM's removes friction for the user. Travelers no longer have to piece together information from multiple websites. The AI will do that for them, delivering a curated answer. Early adopters of AI trip-planners report a more intuitive experience. It’s like talking to a savvy local or a personal concierge, except it’s available on-demand. And the technology is improving rapidly. We’re seeing the first versions now: semi-autonomous agents that still hand off to a website for final booking steps. But the vision (and likely not far off) is that soon the AI chat could complete bookings end-to-end. In fact, OpenAI has already enabled ChatGPT to execute web actions in certain cases. E.g. to search and book a restaurant reservation via plugins). Imagine asking your voice assistant to find and book a hotel for next weekend and it just does it, presenting you with a confirmation number. 

For hotels, this trend should be exciting, but it also presents a challenge. It upends the traditional funnel where you could intercept the customer at multiple points (search ads, SEO content, OTA listings, etc.). In a chat-driven journey, the AI might only mention a handful of hotels. If you’re not one of them, you don’t exist to that traveller. And unlike a Google results page where maybe you could still appear as the fifth or sixth result and get some clicks, an AI will likely focus on one or two recommendations, unless specifically asked for more results. It’s a winner-takes-all scenario for attention. This raises the stakes for being included in that answer.

It’s also worth noting that AI recommendations won’t be perfect, at least not yet. Today’s conversational models have notable limitations: they can sometimes produce outdated info or even fabrications. One recent test of Meta’s new travel chatbot found that it confidently recommended two restaurants that had permanently closed. No hotel wants to be on the wrong end of that kind of mistake. However, the overall direction is clear: each month these AI systems are getting more accurate, more integrated, and more popular with consumers. Sceptics might point out that many travellers still use Google or rely on OTA sites; and that’s true, for now. But remember how quickly online travel agencies went from novelty to dominance in the 2000s, or how mobile booking surged in the 2010s. We’re likely at the start of a similar shift. The hospitality leaders who experiment early and learn how to work with AI assistants will have a competitive edge if (or more likely; when) this behaviour goes mainstream.

Hotel Groups vs. Independent Hotels: Who Has the Edge in GEO?

Will large hotel chains have an unfair advantage in this new AI-driven landscape? In some ways, yes. Big brands do have a head start. Major hotel groups possess a wealth of structured data and content and they have entire teams managing their digital profiles. This means they can more easily ensure every property is represented consistently across the web, with proper metadata, updated descriptions, and integration into platforms like Google Hotel Ads. But most everyone likely already feeds their rates and inventory into multiple channels (OTAs, GDS, metasearch). Extending that to an AI assistant is just one more integration. One reason Kayak’s AI can deliver live bookable results is that it’s hooked into global distribution systems and direct connections with hotel chains. Though big brands are also more likely to have internal AI projects (or partnerships with tech companies) to develop their own chatbots or voice assistants. |So it is fair to say that large hotel groups can throw resources at GEO in a way independents cannot.

However, it would be a mistake for independent and boutique hotels to assume they’ll be left behind. In the era of GEO, nimbleness and niche appeal can level the playing field. Remember that AI models are scouring the entire internet for information. A small hotel with a compelling story and strong local buzz can get on the AI’s radar just as much as a big brand. If not more so, if there’s a unique angle. In fact, independent hotels often excel at generating the kind of authentic, engaging content that AI algorithms love. Think about the rich narratives in guest reviews, or a feature in a local travel blog about that charming B&B on the coast. LLMs treat those human voices and unique content as valuable signals. In contrast, big chains sometimes have more generic, copy-paste style content for all their properties, which might not stand out to an AI.

Crucially, GEO isn’t pay to play. Unlike Google where large brands can dominate ad space and afford extensive SEO campaigns, an AI model doesn’t care about your marketing budget. It cares about knowledge and reputation. An independent hotel with top-notch guest satisfaction and loads of 5-star reviews might actually look more attractive in an AI’s eyes than a branded hotel with middling feedback. Thousands of positive reviews mentioning your hotel’s name make it “unmissable” to the model processing travel advice. Independent properties should capitalize on this by actively encouraging reviews on Google, TripAdvisor, and other platforms, and (maybe more importantly) by engaging with those reviews. Responding to reviews not only shows good service to potential guests (improving GRI), but those responses themselves are content that an AI can pick up about how attentive you are.

One challenge for small hotels is technical integration. A big chain might eventually plug its central reservation system into an AI platform’s interface. An independent hotel probably won’t have a direct OpenAI plugin or a custom AI API integration. But you don’t necessarily need your own plugin to benefit. By ensuring your hotel’s information is distributed through channels that do integrate with AI (for example, making sure you’re bookable via Expedia, Booking.com, or Google’s booking links), you ride along with those larger integrations. In the long run, industry standards may emerge for feeding data to AI assistants, possibly via schema markup or open APIs for availability. When that day comes, it might actually be handled by PMS (Property Management System) vendors or channel managers that even small hotels use. So independents should stay alert but not panic: focus on the data and content you can control.

Finally, consider the local context advantage. Big chains have brand recognition, but travellers often ask AI very specific, personalized questions. Like; “Which hotel has the best view of the fireworks from the harbour?” or “Is there a boutique hotel in this neighbourhood with a free airport shuttle and a vegan breakfast?” If you are the hotel that fits a very specific niche, and you’ve made that known in your content and online footprint, the AI might surface you as the ideal answer. What matters is that the AI knows about it.

Tactics to Optimize for GPT-Based Recommendations (GEO)

If the traditional SEO playbook revolved around keywords and backlinks, the GEO playbook will include new tactics on top of those basics:

• Implement Structured Data (Schema Markup): Make your website as machine-readable as possible. Use schema.org markup for hotels, include your location, star rating, amenities, review snippets, and any other relevant attributes in the code. This structured data helps search engines and AI models understand factual details about your property. If your site clearly labels you as a “4-star hotel with pet-friendly rooms and canal views,” an AI can more confidently recommend you for queries seeking those features. Additionally, structured data feeds knowledge graphs (like Google’s), which are likely tapped by AI systems for up-to-date info. So, don’t just hope the AI parses your beautifully written paragraph, but serve it the facts on a silver platter.

• Provide Real-Time Data through APIs (Rates & Availability): A key difference with AI-assisted travel planning is the expectation of immediacy. Travellers will want to know not only which hotel they should book, but “Is it available for my dates, and what’s the rate?” right within the chat. Hotels should prepare for a future where connectivity with AI platforms becomes standard. This might mean participating in new integration programs, being part of Google’s own hotel API or ensuring your channel manager feeds accurate rates to all distribution platforms. This will position you to be bookable when an AI asks for “2 rooms next weekend under $300/night.” We’ve already seen hints of this: Kayak’s AI can surface bookable options inside the chat because it’s connected to reservation system. Hotels should keep an eye on developments like ChatGPT plugins for travel and be ready to plug in when the opportunity comes. In practical terms, talk with your technology providers about how they’re preparing for AI channels. You don’t want to be the one property that’s omitted from an AI-generated itinerary because your data wasn’t accessible.

• Publish High-Quality, Conversational Content: Content remains king for GEO, but the style of content that wins might be a little different. Large language models favour content that is clear, conversational in tone, frequently updated, and information-rich. This is a good time to refresh your website copy, blog posts, and FAQs to ensure they sound natural and answer real questions. Embrace a more Q&A style in some of your content: for example, write a detailed FAQ section or a blog post addressing “Which rooms have the best views of the harbour fireworks at our hotel?” If travellers are asking a question out loud, try to have that question (and answer) indexed on your site or on a platform the AI can read. Authoritative content is also crucial – be the source that gets quoted. If your city’s tourism blog or a major travel publication features your hotel in an article, that’s fantastic fodder for AI. These models also love unique descriptions and stories, so highlight what makes your property one-of-a-kind (in a genuine way).

• Boost Your Digital Footprint via Guest Reviews and Earned Media: In an AI-driven world, what others say about you carries heavy weight. More than just word-of-mouth marketing. Encourage guests to leave reviews on Google, TripAdvisor, Yelp, and other prominent platforms. These reviews are not just for human eyes anymore, but for AI training data too. A large volume of positive (and detailed) reviews will make your hotel stand out when the AI has “learned” about travel options. Moreover, respond to reviews and engage in forums or Q&As when people mention your hotel. Each mention increases the likelihood that an AI associates your name with a positive experience or particular niche. Don’t forget more traditional PR and content either: being featured in local news, travel blogs, or lists like “Top 10 boutique hotels in X” improves your authority signals in the eyes of AI. These models treat presence across trusted sources as a sign of reliability. In essence, the more places your brand appears (in a meaningful way), the better your AI visibility.

• Leverage Google and OTA Platforms: Even if travellers start using ChatGPT, the information it provides often originates from the same places that feed Google and OTAs. Make sure your hotel is fully optimized on Google’s own ecosystem. This means Google Business Profile (with up-to-date info, photos, and regular posts), Google Maps reviews, and participating in Google Hotel Ads or the free booking links. Content from those sources likely informs Google’s AI and others. Likewise, keep your listings on OTA channels like Booking.com, Expedia, Hotels.com, TripAdvisor etc. thorough and up to date. It’s no coincidence that when ChatGPT answers a travel question, it often pulls data or citations from those major travel sites. One report noted that Expedia and Kayak’s early ChatGPT integrations were intended to feed the chatbot high-quality data to make planning easier, which implies that if your property is well-represented on those platforms, the AI has more to work with. Similarly, any structured content you provide to metasearch (like amenity details, property descriptions in multiple languages, etc.) could end up as part of the AI’s knowledge.

Stay Ahead: Questions Hoteliers Should Be Asking

The rise of GEO is still in early days, which means proactive hoteliers can shape how this plays out. A smart way to start is by asking the right questions within your team. Here are a few to consider:

• “How does ChatGPT (or Bard, etc.) currently describe or rate our hotel?”: Go ahead and ask these AI tools about your property. Are they even aware of it? Do they mention accurate details? Treat any AI response as a kind of audit of your digital footprint. If the AI spits out outdated or incorrect info, that’s a sign you need to push fresh data and content out to the web.

• “What new channels or integrations should we pursue to connect with AI-driven travellers?”: For example, should you participate in Google’s pilot programs for AI-generated travel answers? Are there partnerships with booking engines or start-ups that would include your inventory in AI assistants? Keep an eye on announcements from tech providers (PMS, CRS, channel managers) about AI connectivity. You don’t want to miss the boat.

• “Is our hotel content and data ‘AI-friendly’?”: This is a broad question touching on many areas: Do we have schema markup in place? Are our website and booking engine easily crawlable? Do we have a robust FAQ that addresses common guest questions? Are we active on the platforms that an AI is likely to consider authoritative (Google, major OTAs, destination guides)? Essentially, if an AI tried to learn everything it can about us today, would it find a treasure trove or scraps? Identify the gaps and make a plan to fill them.

• “How can we encourage more genuine, detailed guest feedback online?”: Since reviews and social chatter are so influential for AI recommendations, think about initiatives to boost them. This could be as simple as engaging with guests post-stay to leave a review, or as creative as running a contest for the best Instagram caption about your hotel (user-generated content can feed AI, too).

• “What if the booking process flips overnight?” This is a thought experiment: imagine that a year from now, 30% of your direct bookings actually start from an AI assistant query. Would your current digital strategy capture those, or would they slip to an intermediary (or worse, to a competitor)? Do you need to negotiate new agreements with OTAs regarding AI-driven bookings? Should you allocate some marketing budget to experimenting with AI chat advertising or sponsorship if that becomes a thing? Essentially, are you prepared if consumer behaviour shifts quickly? The hospitality sector has been caught off-guard before by sudden shifts (think of how mobile booking rose, or how meta-search became vital). This time, we have a bit of foresight.

  
  

A healthy dose of scepticism is warranted, of course. Not every shiny tech trend transforms our industry, but in our industry we have been talking about it for years, and we know guests are picking up AI tools now more than ever. The cost of experimenting in GEO is relatively low, since it’s mostly about refocusing your digital efforts and staying informed. The cost of ignoring it, however, could be high if AI-driven bookings do take off while your hotel remains invisible to the new “gatekeepers.”