How to write AI Search optimized content for hotels

Getting your hotel’s content and brand included in generative AI answer engines for relevant prompts comes down to ensuring it’s crawlable, well-structured, answers questions concisely and directly, and is contextually rich. But how does your hotel produce or revise its content to ensure it’s best structured for visibility in AI search engines?

Our team has put together this guide on how to write content that is well optimized for AI search engines, but doesn’t ignore the importance of traditional search engine optimization, which is still an essential tool for brand success and bookings. 

1. Ensure each page is focused on a specific topic or intent focus

LLMs prefer clearly presented and specific content that answers a question. Prioritize developing pages focused on a specific topic, then answer that question directly and thoroughly.

Examples of pages with a clear, specific focus:

• Location page: focuses on specific information, providing direct answers about where this hotel is and what is nearby, including attractions, demand drivers, the airport, and more.
• Amenities page: what does this hotel offer, and who is it best for
• Pet-friendly page: highlights the policies and reasons why your hotel is a great choice for people travelling with pets

Tip: Avoid mixing sales copy, policies, and other content that doesn’t directly answer that intent

2. Consider using a standard, repeatable content format designed for LLMs and humans

Well-formatted content is not only beneficial for LLMs and AI visibility but also preferred by humans! It’s critical not to lose sight of optimization for people as well as bots. This structure enables AI engine bots to crawl and consume content in chunks while allowing humans to quickly scan and find the information and answers they are looking for on the topic.

An example of great LLM (and human) structured content could look something like:

These are a few examples of hotel page content structure types that do this well:

• Prompt: luxury Aspen hotels
  • Sources Cited by LLMs:
    • https://avantgardeaspen.com/blog/the-best-luxury-accommodations-in-aspen-colorado-5-star-hotels-and-exclusive-vacation-rentals-or-avant-garde-aspen-luxury-real-estate
    • https://www.aspentraveladvisors.com/luxury-ski-hotels 

• Prompt: Hotel near Point Loma San Diego
  • Sources Cited by LLMs:
    • https://www.fodors.com/world/north-america/usa/california/san-diego/neighborhoods/point-loma-and-coronado/hotels
    • https://point-loma-inn-suites.thesandiegohotels.com/en/
    • https://all-boutique-hotels.com/san-diego_point-loma/ 

• Prompt: Historic Nashville Hotel
  • Sources Cited by LLMs:
    • https://thehermitagehotel.com/historic-hotel-nashville/first-5-star-hotel/
    • https://www.unionstationhotelnashville.com/historic-hotel-in-downtown-nashville-tn/
    • https://www.marriott.com/en-us/hotels/bnaak-the-union-station-nashville-yards-autograph-collection/overview/ 

3. Your page intro paragraph should stand alone as an answer

A great start to an LLM (and human) structured content page is to use your opening paragraph as a standalone answer. Follow these guidelines:

• Strong intro paragraph rules for your hotel’s page
  • 2–3 sentences max
  • Clear, specific language (avoid vague, marketing language)
  • Directly answers what, where, and who

• Example (for your hotel’s location page intro paragraph)
  • ❌ “Experience the perfect blend of comfort and convenience in the heart of the city.”
  • ✅ “The hotel is located in downtown Denver, two blocks from Union Station and within walking distance of restaurants, museums, and public transit.”

4. Treat each H2 section as an “answer node”

LLMs prefer a direct and clear response to a specific question. Use your page’s H2 header tags to do just that. Here’s how you can approach using your page’s H2s to answer specific questions or topics:

Here are some good H2 examples for your hotel’s content:

• “Where the Hotel Is Located”
• “Parking and Transportation Options”
• “Who This Hotel Is Best For”
• “Nearby Attractions and Distances”
• “What Guests Should Know Before Booking”

Here are some poor H2 examples for LLMs:

• “Why You’ll Love Staying With Us”
• “A Truly Unique Experience”
• “Luxury Redefined”

Optimizing page content for LLMs can produce similar concerns as optimizing for search engines. These bots prefer direct, informational text, which can conflict with a hotel brand’s preferred language and brand voice on the page. It’s important to consider this impact from both an AEO/SEO perspective and a brand voice perspective. 

Tip: If an H2 cannot be phrased as a question, it’s probably weak for AI search optimization.

5. Keep paragraphs short and to the point

Just like humans in today’s short-attention-span world, LLMs prefer short and concise answers. Use this to guide your page’s paragraph length.

• Keep your page’s paragraph content to 2–3 sentences max
• Focus on answering just one idea per paragraph
• Utilize concrete details over adjectives or marketing jargon

Here’s an example showcasing a poorly crafted paragraph for LLMs vs a well-optimized one:

• ❌ “Our hotel offers convenient access to Nashville attractions while providing guests with a peaceful and comfortable stay thanks to our attentive staff and thoughtful design.”
• ✅ “The hotel is within a 10-minute walk of downtown Nashville attractions. Many guests choose the property for its quieter rooms compared to other downtown hotels.”

6. Use lists and tables

LLMs prefer content that is easily consumable in the format of tables, bullets, and numbered lists. This is because content formatted as lists helps LLMs identify attributes, steps, and groupings. As a human, it also makes the content much easier to scan, consume, and find what you’re looking for.

Here are a few ideas on the best uses for lists on your hotel’s pages:

• Amenities
  • Room features
  • Policies
  • What’s included / not included
  • Itinerary steps

Here’s a specific example for a hotel’s amenities page list section:

• Amenities Include:
  • Complimentary Wi-Fi throughout the property
  • On-site fitness center
  • Underground self-parking (daily fee)
  • Pet-friendly rooms (fee applies)
  • This format makes it easy for AI to extract and restate.

7. Include a list of FAQs at the end of the page

Tieing into the understanding that LLMs prefer concise answers to specific questions, tap into this by adding a short FAQ content block to the end of your hotel’s page. When adding FAQs to your page, make sure to:

• Add around 3-5 FAQs
• State the question followed directly by a specific, informative answer
• Make sure the FAQs are related to answering questions about that page’s specific intent or topic

8. Use a natural language URL structure

The impact of keywords within URLs has diminished over time when it comes to traditional SEO. Interestingly enough, the use of natural language and specific keywords in URLs is proving to be more important for LLMs and AI search. Make sure to incorporate the full title of your content piece and use semantic URLs. 

Here are a few good semantic URL structure examples:

• /best-family-friendly-activities-san-diego/
• /things-to-do-san-diego-mission-bay/
• /2-bedroom-san-diego-hotel-suite/

Here are a few examples of poor URL structure:

• /post?categoryid=18456
• /page13
• /product/roomtype1

9. Update past content and the publish date

Recency of content and publish date influence visibility in AI search. This includes revisiting and updating past content, such as itinerary guides and blogs, to reflect new information. Along with updating the content, make sure to update the publish date on the page. 

10. Avoid JavaScript for rendering important page content

JavaScript-heavy pages are less likely to be cited or summarized in AI search engines. LLMs and AI crawlers prefer static pages and more often extract content from HTML. While JavaScript is acceptable for uses such as UI, form validation, and analytics, it should be avoided for rendering main content on the page or loading your hotel website’s primary navigation. 

11. Incorporate citations and quote sources

Answer engines like Google AI Overviews and ChatGPT prioritize fact-based, well-sourced, and contextually reliable content. Citations and direct quotes support your content and signal credibility. For hotels, this can include:

• Quoting and linking to guest reviews
• Trust signals from awards like Conde Nast or TripAdvisor, and linking to the award page on the publisher
• On-property policies, certifications, and features that are verified by a 3rd party organization 

Bonus tip: Looking for new content ideas, such as itineraries, features, amenities, and demand drivers that are important to your potential guests? Dig into your guest sentiment analysis to extract real guest insights on the likes, dislikes, reasons to stay at your property, and more.

AI doesn’t rank hotels. It learns which ones to trust.

In our last post, "Why AI visibility ultimately collapses back to data", we made the case that AI visibility ultimately collapses back to data.

That idea challenges a lot of current thinking. It reframes AI discovery as something earned over time rather than optimized into existence through prompts, schema, or surface-level tactics.

But it naturally raises a more important question:

If AI systems infer visibility from data, what does brand authority actually look like in an AI-driven travel market?

Authority is inferred, not declared

Hotels don’t tell AI systems that they are authoritative. AI systems infer authority from patterns.

Those patterns are built over time and reinforced across many signals:

• How consistently a hotel shows up
• How often travelers choose it
• How reliably it delivers on expectations
• How well its signals align across platforms

In an AI-driven world, authority isn’t a claim. It’s a pattern that emerges when data agrees.

A single strong signal can’t carry authority on its own. If engagement says one thing, availability says another, and pricing or reputation contradicts both, AI hesitates. And hesitation reduces visibility.

We’ve been here before

This isn’t the first time marketers have gone through a shift like this.

When Google first introduced PageRank, it fundamentally changed how visibility was earned. Ranking wasn’t determined by how many times a keyword appeared on a page. It wasn’t even primarily about how well-written a website was. It was about signals of credibility and relevance across the broader web.

Many people tried to game that system through keyword stuffing, link schemes, and other shortcuts. Some of those tactics worked temporarily. Most didn’t last.

What ultimately mattered was whether a site was referenced, trusted, and reinforced by other credible sources over time.

In many ways, we’ve come full circle.

The difference now is that visibility is no longer centered on a single website. AI-driven discovery doesn’t evaluate brands based solely on what lives on their domain. It evaluates them based on how they show up across the entire digital ecosystem.

This time, it’s not about ranking pages. It’s about understanding brands.

AI systems are inferring authority not from isolated signals, but from a hotel’s broader presence, performance, and consistency across channels. The same pattern applies: shortcuts may appear tempting, but durable visibility is earned through trust, reinforcement, and alignment over time.

Signal coherence matters more than channel coverage

Many hotels worry about being everywhere. Every platform. Every new AI surface. Every emerging discovery channel.

But AI doesn’t need you everywhere. It needs your signals to agree.

Brand authority is inferred when a hotel’s identity, positioning, and performance signals are coherent across the places travelers research, compare, and book. That coherence matters more than sheer coverage.

AI systems are looking for corroboration:

• Does this hotel look like the same entity across sources?
• Do pricing and availability signals align?
• Does performance reinforce positioning?

Authority doesn’t come from owning every channel. It comes from avoiding contradictions across them.

Performance is the strongest authority signal

AI pays close attention to what travelers actually do.

Engagement, conversion, and booking behavior matter more than how well something is described. Over time, AI learns which hotels are consistently selected, which satisfy intent, and which reinforce positive outcomes.

This is why performance-based signals are so powerful:

• Repeated selection
• Sustained conversion
• Repeat behavior
• Strong review velocity tied to actual stays

AI doesn’t just listen to what a hotel says. It watches what travelers choose.

And while short-term spikes may get noticed, it’s long-term patterns that establish authority.

PR as an authority signal

Brand authority isn’t built through owned channels alone. Third-party validation plays an important role in how trust is inferred.

When hotels are consistently referenced by respected publications, destination guides, and industry voices, those mentions act as corroborating signals. They reinforce credibility in the same way strong performance does, by validating a hotel’s positioning outside of its own marketing channels.

In an AI-driven discovery environment, effective PR isn’t about press hits for their own sake. It’s about earning references that clarify who a hotel is, what it’s known for, and why it should be trusted. These third-party signals help reinforce brand authority in the broader ecosystem AI systems learn from.

Inconsistency erodes trust faster than invisibility

One of the fastest ways to undermine brand authority in an AI-driven ecosystem is inconsistency.

Small misalignments that may seem manageable in isolation can quietly erode trust:

• Pricing patterns that contradict positioning
• Availability signals that don’t align across systems
• Attribute drift between platforms
• Messaging that promises experiences not reinforced by outcomes

In an AI system, inconsistency creates hesitation. And hesitation reduces confidence.

For hotels, this doesn’t mean perfection is required. It means contradictions shouldn’t go unnoticed or unresolved.

Authority is built through reinforcement, not optimization cycles

AI systems learn over time. They reward stability, predictability, and reinforcement.

This creates an important shift in mindset. Constant reinvention, frequent pivots, and isolated optimization efforts can actually weaken authority by disrupting signal continuity.

The hotels that win aren’t constantly trying to redefine themselves. They’re consistently reinforcing who they are, how they perform, and what travelers can expect.

Authority compounds when signals are stable and outcomes reinforce them.

Where most hotels get stuck

Most hotels don’t lack brand authority. But they do lack visibility into whether their signals agree and how those signals are interpreted beyond their own name.

For years, hotel marketing has been shaped by a very real constraint: domain authority and scale. Independent and boutique hotels have long struggled to compete with branded properties and OTAs for destination-level keywords. Even when a hotel ranks well for its own name, visibility for broader market and destination searches has often been out of reach.

That challenge hasn’t disappeared. But the way authority is inferred is changing.

AI-driven discovery is less focused on the raw authority of a single domain and more focused on whether a brand is consistently understood, referenced, chosen, and reinforced across the ecosystem. This shifts the problem from how big your website is to how coherent your brand signals are.

This is where many hotels get stuck.

Data lives in silos. Teams optimize individual channels in isolation. Performance is measured, but not always connected back to discovery, reputation, or trust. As a result, authority is something hotels know they have in practice, but struggle to see, manage, or reinforce systematically.

The challenge in an AI-driven market isn’t creating authority from scratch. It’s understanding how existing authority shows up beyond branded searches, and sustaining it consistently across the signals AI systems actually observe.

What comes next

If brand authority is inferred from coherent, performance-backed signals, the next question becomes operational:

How do hotels see, validate, and reinforce those signals at scale?

In our next post, we’ll explore how data platforms make brand authority measurable, sustainable, and durable in an AI-driven travel market, and why they are becoming foundational to long-term AI visibility.

Why AI visibility ultimately collapses back to data

There’s no shortage of buzz around AI right now. Large language models (LLMs), generative search experiences, and “AI optimization” tactics are dominating conversations across hospitality marketing.

And the excitement is justified. AI is already changing how travelers discover hotels, evaluate options, and make booking decisions. For marketers and hoteliers alike, there are real opportunities to adapt content, refine messaging, and improve visibility inside these new interfaces.

But beneath the surface, something more fundamental is happening.

In the long run, winning in AI visibility will always tie back to data.

Not prompts. Not hacks. Data.

AI doesn’t create authority; it infers it

LLMs don’t “decide” what to recommend in the way a human does. They infer authority, relevance, and trust from patterns in data.

That distinction matters, especially as the race to build AEO offerings has led many teams to focus heavily on executional tactics like schema markup and FAQs. Those elements are important, and they play a meaningful role in helping AI interpret information. But they are not sufficient on their own.

AI systems don’t treat authority as a checkbox. They infer it from signals accumulated over time.

Those signals come from many places:

• Structured data that clearly defines what a hotel or brand is
• Consistency across platforms and sources
• Behavioral signals like engagement, conversion, and booking patterns
• Historical performance and reliability

Together, these inputs form a picture of brand authority. Not just what a hotel claims to be, but how consistently it shows up, how often it’s chosen, and how reliably it delivers on guest expectations.

This is why brand authority matters more than any single optimization tactic. Schema and FAQs help AI interpret information, but authority is what gives that information weight.

For hotels, building brand authority in an AI-driven world is less about chasing visibility and more about reinforcing fundamentals:

• Showing up consistently wherever travelers research, compare, and book stays, from search and maps to metasearch, OTAs, and review platforms
• Delivering guest experiences that drive strong engagement, positive reviews, repeat stays, and direct bookings
• Maintaining accurate, aligned property data across websites, booking engines, metasearch, listings, and third-party channels
• Earning trust over time through pricing integrity, reliable availability, and guest satisfaction, not marketing promises

When data is incomplete, inconsistent, or outdated, AI systems hesitate. When brand authority is weak or fragmented, recommendations become generic or disappear altogether. Over time, no amount of surface-level optimization can compensate for that gap.

AI doesn’t reward those who publish the most structured data. It rewards the brands whose data reflects real-world trust, consistency, and performance.

Short-term wins come from tactics. Long-term wins come from systems.

Right now, it’s possible to gain incremental AI visibility through tactical efforts:

• Adjusting content to align with AI-driven queries
• Experimenting with prompt-oriented optimization
• Tweaking page structure, schema, and language

These efforts matter, especially during periods of change. But they are, by definition, short-lived advantages.

As AI systems mature, they increasingly favor structure over tactics:

• Clean, structured data
• Measurable outcomes
• Proven performance
• Signals that persist over time

The hotels that win aren’t optimizing for the moment. They’re building durable data foundations that compound.

AI discovery is entity-based, not keyword-based

Traditional search trained marketers to think in keywords. AI shifts the frame entirely.

Large language models don’t retrieve answers by matching exact phrases. Instead, they interpret prompts as questions about entities and the relationships between them.

When a traveler types or speaks a prompt like:

• “What’s the best family-friendly resort near Yellowstone?”
• “Where should I stay in Napa for a romantic weekend?”
• “Which hotels near downtown Austin have great food and easy parking?”

The model isn’t looking for pages optimized around those exact words. It’s reasoning through a network of relationships:

• Location
• Property type
• Amenities and experiences
• Guest intent
• Historical performance and reputation

In that context, a hotel isn’t just a website. It’s an entity defined by data:

• A physical location
• A brand and reputation
• A set of amenities and experiences
• A pricing and availability profile
• A history of guest satisfaction and outcomes

This is where prompts are often misunderstood.

Prompts don’t create visibility on their own. They only surface what the model already understands. If an AI system doesn’t have clear, consistent, and trusted data describing those entities and relationships, no amount of prompt optimization can reliably compensate.

When relationships aren’t well defined in data, AI hesitates. Recommendations become generic, incomplete, or disappear entirely. Visibility suffers not because a hotel is “missing keywords,” but because the system can’t confidently understand what it is, how it fits the request, or why it should be recommended.

In an AI-driven world, prompts are simply the question. Data determines the answer.

Where AEO fits in a data-first AI strategy

This is where Answer Engine Optimization (AEO) plays a critical role. Not as a collection of prompts or AI shortcuts, but as the discipline of structuring, validating, and distributing trusted data so AI systems can accurately understand and represent a property.

Done correctly, AEO operationalizes a data-first approach. It ensures that entity relationships, performance signals, and guest experiences are translated into formats AI systems can confidently use across the places travelers increasingly rely on for discovery.

Distribution now matters more than optimization

For years, the hotel website was the center of gravity. Today, it’s just one node in a much larger ecosystem.

AI systems pull signals from everywhere:

• Booking engines and transaction platforms
• Reviews and reputation sources
• Local listings and business profiles
• Feeds, APIs, and structured data sources
• Historical demand and conversion data

Visibility is no longer about perfecting a single destination. It’s about ensuring accurate, consistent data flows across the entire ecosystem where AI learns, validates, and reinforces information.

Feedback loops are the real competitive moat

The most powerful advantage in AI discovery isn’t being understood once. It’s being learned from repeatedly.

AI systems reinforce what works:

• What gets selected
• What converts
• What satisfies traveler intent
• What performs consistently over time

That requires clean measurement, reliable attribution, and closed-loop data systems. Without those feedback loops, hotels remain static in AI models. With them, visibility compounds.

The real shift hoteliers must confront

AI isn’t replacing marketing. It’s changing what marketing is built on.

Content still matters, but it’s becoming a translation layer. Technology still matters, but it’s becoming infrastructure. Data is becoming the source of truth and leverage.

For hoteliers, this shift is critical. AI-driven discovery will increasingly favor properties that can clearly and consistently describe who they are, what they offer, where they’re located, and how they perform across every platform where travelers research and book.

The hotels that win in AI won’t be the ones asking how to game the system. They’ll be the ones building brands and data foundations that the system trusts.

LLMs may change the interface travelers use to find you. Your data will determine whether you show up at all and how you’re positioned when you do.

In our next post, we’ll break down what brand authority actually looks like in an AI-driven travel market and how hotels can influence the signals AI relies on…