The Discovery Revolution and Why Skeptics Are Wrong
Why This is Not Cyclical Noise
When you walk into your monthly budget meeting and face harsh questions about why organic search traffic dropped 15% despite maintaining the same SEO spend, or when your quarterly ownership meeting demands explanations for declining click-through rates with unchanged or increased PPC budgets, you experience the symptoms of a fundamental structural shift that many hospitality executives still dismiss as temporary noise.
The data tells an unambiguous story. Pew Research Center's March 2025 study, based on actual user behavior analysis rather than marketing speculation, found that just 1% of users click links within AI summaries themselves. Not 10% or 5%.One percent. When AI Overviews appear in Google search results, traditional organic click-through rates plummet from 15% to just 8%.
This is not a gradual shift you can adapt to over time. It is a cliff. Bain & Company reveals that roughly 80% of search users rely on AI summaries for at least 40% of their queries, leading to a 15% to25% reduction in organic web traffic. This shift, according to SparkToro, has resulted in ~60% of traditional search engine queries ending without a click-through to another website. A Siteminder report shows that 78% of travelers intend to use AI in trip planning or during their hotel stays. Expedia Group reports nearly 40% of global travelers would be likely to use AI to help find the perfect stay. These aren't early adopters. This is mainstream consumer behavior that is occurring while most hoteliers focus on traditional metrics.
For skeptics who believe this is vendor-driven hype, consider this. Google did not invest billions in AI Overviews to improve advertiser ROI. They deployed this technology in alignment with observed user behavior shifts toward answer-seeking rather than link-clicking. Per Google's own help documentation, advertisers can't directly target AIOverview placements, and there is no segmented reporting for those placements.
You’re Losing Revenue You Can’t See
The most dangerous aspect of this shift is what you can’t measure. Traditional analytics show you the last click before conversion, not the discovery moment that created awareness. A guest who finds your hotel through ChatGPT, validates it on TripAdvisor, checks rates on Google, and then books directly appears in your analytics as a direct booking success. In analytics, it appears as “direct” but in reality, it began in an AI answer.
This creates “The Visibility Gap,” a chasm between actual influence and measurable attribution. Traditional tracking can’t tell you if you are considered or rejected in AI answers. Google explicitly confirms that advertisers can’t directly target AI Overview placements, and there is no standard analytics revealing when a model “considered and rejected” your property.
If 40% of your target travelers use AI for initial hotel research, and you’re invisible in AI responses, you’re effectively excluded from nearly half your potential market before they even know you exist. Unlike traditional SEO where you might rank on page two and still capture some searchers, the more information in the prompt query, and the more optimized a hotel's online pres-ence, the more likely the AI is to deliver several relevant hotel recommendations. If you aren’t included, you're completely absent from consideration.
This differs fundamentally from what social media and OTAs once offered. While platforms like Instagram and TripAdvisor also created attribution challenges and shaped consideration sets outside your direct analytics visibility, they traditionally functioned as traffic drivers. A traveler influenced by an Instagram post or TripAdvisor review would typically click through to your website, creating at least some measurable referral source. However, this model is rapidly hanging as all major platforms now prioritize retention over referral traffic, fundamentally altering how discovery and influence operate across the digital landscape.
“Travelers are no longer typing filters or clicking through 10 blue links —they’re asking AI to find the perfect stay,” said Brad Brewer, CEO and ChiefAI Officer, Agentic Hospitality. “With 40% of global travelers already relying on AI recommendations, hotels can’t afford to treat visibility as an afterthought. By 2026, the booking widget era will be over, with 90% of informational prompts answered on AI surfaces. Natural language will prevail, ushering in conversa-tional commerce never before seen on the web. Structured content, real-time rates, and loyalty-driven offers must live inside AI surfaces, or the guest journey will default back to intermediaries — this time led by OpenAI, Gemini, Manus, Claude, and Perplexity.”
A NEW DISCOVERY FRAMEWORK
To understand this shift, I developed the Answer Spiral, a fundamental reconceptualization of how travelers actually discover hotels in the AI era. Unlike the linear marketing funnel that assumes customers move predictably from awareness to consideration to purchase, the AnswerSpiral recognizes that AI-mediated discovery is cyclical, iterative and increasingly compressed.
The Answer Spiral consists of six interconnected stages that repeat in shrinking cycles until travelers find their answer.
- Prompt - The traveler initiates discovery through natural language questions like “family-friendly hotels near Disney World with pools” rather than keyword searches like “hotels Disney pools.”
- Retrieval - AI engines scan training data, conduct real-time web searches, access structured databases, and query partner APIs to gather relevant information about hotels matching the prompt parameters.
- Synthesis - The AI processes retrieves information, validate consistency across sources, evaluates relevance and authority, then constructs a response that typically includes a curated set of hotel recommendations with supporting details. The number varies based on query specificity, platform design and user context.
- Mention-Your hotel either appears in the generated response with specific details and positioning, or faces complete exclusion from consideration without any visibility into the decision process.
- Action - The traveler may request more details, modify their prompt for additional options, click through to review sites, or transition to booking platforms based on AI-generated awareness.
- Feedback-AI engines incorporate engagement signals such as did users find the response helpful, did they click through, did they ask follow-up questions to improve future recommendation accuracy.
Each spiral iteration becomes more focused and specific. If your hotel appears in early iterations, you build momentum toward booking consideration. If you're excluded, subsequent spirals typically reinforce that exclusion, creating cumulative visibility disadvantage over time.
WHY THE SPIRAL MODEL MATTERS MORE THAN THE FUNNEL
The traditional marketing funnel assumes customers enter at the top(awareness) and progress linearly downward through consideration, intent and purchase. The Answer Spiral recognizes that AI discovery compresses these stages into single interactions where awareness, consideration, and initial intent formation occur simultaneously within AI-generated responses.
This compression creates new competitive dynamics. Instead of competing for attention across multiple touchpoints over weeks or months, hotels now compete for inclusion in specific AI responses that shape immediate consideration sets. The window for influence has narrowed dramatically while the stakes for inclusion have increased proportionally.
WHY UNKNOWN PROPERTIES FACE EXTINCTION
Across platforms tested by Cloudbeds, 72.4% of AI-recommended properties were branded, with a +4.43 percentage point visibility advantage over independents. This seemingly small difference compounds rapidly across thousands of traveler interactions.
If travelers already know your brand, you will likely appear in AI responses when they ask about your market. If they don't know your brand, you face exclusion from discovery, creating a vicious cycle where unknown properties become increasingly invisible while branded hotels strengthen their recognition advantage.
For independent and boutique properties, this trend represents an existential threat. Unlike traditional search where smaller properties could compete through local SEO, niche positioning or specialized content, AI engines tend to favor entities with broad recognition across multiple authoritative sources. The algorithms inherently bias toward “safe” recommendations with established reputations through entity consistency and cross-source authority mechanisms.
This isn't theoretical speculation. Testing across major AI platforms reveals consistent patterns. Branded chains appear in 60-70% of relevant prompts, while comparable independent properties appear in 20- 30% of identical queries. The visibility gap translates directly into consideration set exclusion for properties that would previously compete effectively through traditional marketing channels.
THE PLATFORM DEPENDENCY REALITY
Some hospitality executives argue that AI discovery represents temporary technology adoption that will normalize over time, similar to social media or mobile optimization. This perspective misunderstands the fundamental economics driving platform behavior.
Every major platform is now optimizing for on-platform resolution. Google answers questions directly through AI Overviews rather than sending users to websites. Third-party tests suggest that Facebook and Instagram posts containing outbound links underperform algorithmically. LinkedIn studies indicate that updates sending users off-platform receive deprioritized distribution. TikTok, Reddit and emerging platforms engineer experiences that minimize external click-outs.
This represents strategic business design. Platforms generate revenue by capturing and retaining attention, not by facilitating traffic transfers to external sites. The traditional model of publishing content, sharing links and driving traffic operates against the fundamental business incentives of every major discovery platform.
Traditional content marketing, social media strategies and SEO tactics that depend on driving traffic to your website face inherent disadvantage. You aren’t competing against other hotels for traffic. You’re competing against platform revenue models designed to prevent traffic transfer entirely.
WHY TRADITIONAL METRICS MISLEAD
When organic traffic declines month-over-month despite consistent SEO investment, traditional analysis focuses on algorithm changes, competi- tive pressures or technical issues. But the real cause may be fundamental shifts in how travelers discover hotels. As AI engines increasingly provide answers directly within their interfaces, fewer travelers click through to websites during initial research phases.
This creates a dangerous measurement blind spot. Traditional analytics capture only the final stages of discovery, missing the crucial early influence that shapes consideration sets. You don’t have visibility into whether AI engines mention your property when travelers ask “where should I stay in downtown Portland” or exclude you entirely while recommending competitors.
The attribution problem runs deeper than missing data. A guest who asks ChatGPT for hotel recommendations, receives your property in the response, then searches your brand name directly on Google and books through your website appearing in analytics as a direct booking success. The AI influence that created initial awareness remains completely invisible, leading to underinvestment in the optimization activities that actually drive discovery. Traditional metrics now measure outcomes after the most important decision-making has already occurred. By the time travelers reach your website, they have typically already decided you’re worth considering. The battle for visibility now happens earlier — within AI-generated responses that are invisible to you unless tested directly.
Strategic Framework for AI Visibility Dominance
The Visibility Stack (SEO, AEO, and GEO Integration)
To achieve sustainable AI visibility, hotels must optimize across three interdependent layers that form the “Visibility Stack.” Each layer builds on the foundation below while enabling the intelligence layer above, creating compounding competitive advantages that become increasingly difficult for competitors to replicate.
SEO (Foundation Layer) - The Technical Infrastructure Search Engine Optimization (SEO) remains the foundation, although its purpose has evolved beyond ranking web pages. Modern SEO creates the technical infrastructure that enables AI engines to access, understand, and trust your content. Without this foundation, higher-level optimization efforts fail regardless of content quality or strategy sophistication.
Implement valid JSON-LD schema markup and audit robots.txt to allow the AI crawlers you want (e.g., GPTBot, CCBot, PerplexityBot) while blocking those you don’t. Serve critical content via server-side rendering or pre-rendering, since many bots don't reliably execute JavaScript. Optimize page speed and ensure mobile responsiveness so the site performs well for both human visitors and automated crawlers.
Consider adding an llms.txt file to guide LLMs to canonical, up-to-date facts (voluntary compliance, emerging practice). The foundation layer must be pristine because AI engines often access content differently than human visitors. They may request multiple pages simultaneously, process content without executing JavaScript, or access servers from unusual geographic locations. Technical barriers that marginally impact human experience can completely prevent AI access.
AEO (INTEGRATION LAYER) - ANSWER ENGINE OPTIMIZATION
Answer Engine Optimization (AEO) represents a new discipline focused on designing content specifically for AI retrieval, processing and citation. Unlike traditional SEO that optimizes for human readers who might click through to your site, AEO optimizes for AI engines that extract and reuse your content without sending traffic.
This requires fundamental changes in content structure and presentation. Instead of persuasive marketing copy designed to encourage clicks, AEO content provides clear, factual information in formats AI engines can easily parse, extract and synthesize. FAQ sections with JSON-LD (FAQPage, Hotel schema) become critical infrastructure rather than secondary content. Amenity descriptions must balance human appeal with machine readability while maintaining consistent entity names and IDs across Google Business Profile and OTA listings.
Effective AEO implementation involves structured question-answer pairs that directly address common traveler queries, descriptive headers that clearly indicate content topics, bulleted lists for amenities and policies that enable easy extraction, and consistent terminology that aligns with industry standards AI engines recognize.
The integration layer succeeds when AI engines consistently extract accurate information from your content to include in generated responses. Success metrics include citation frequency, accuracy of extracted information and positive positioning within AI-generated recommendations.
GEO (INTELLIGENCE LAYER) - GENERATIVE ENGINE OPTIMIZATION
Generative Engine Optimization focuses on ensuring your content is trusted and prioritized by AI engines when they synthesize responses. This represents the most sophisticated layer of the visibility stack, requiring deep understanding of how AI engines evaluate source authority, validate information consistency and determine recommendation relevance.
GEO optimization involves building authority signals across multiple sources that AI engines consider when making trust decisions. This includes consistent entity mentions across authoritative publications, verified relationships with local landmarks and attractions, positive sentiment patterns in reviews and editorial content, and structured associations with industry organizations and certifications.
The intelligence layer operates through what I call “trust triangulation.” AI engines gain confidence in recommendations when multiple authoritative sources provide consistent information about your property. A hotel mentioned positively across tourism boards, travel publications and review platforms develops higher trust scores than properties with limited third-party validation.
WRITING FOR MACHINES AND HUMANS
Effective AI optimization requires content that serves both human visitors and machine readers. This dual-purpose approach demands significant changes from traditional hospitality marketing copy.
QUESTION-ANSWER ARCHITECTURE
Structure content around specific questions travelers ask rather than marketing messages you want to communicate. Use clear question headers followed by concise, factual answers that AI engines can extract and cite effectively. Instead of “Experience unparalleled luxury in our magnificent suites featuring stunning harbor views and world-class amenities,” use “What amenities are included in harbor view suites? Harbor view suites include private balconies, separate living areas, complimentary Wi-Fi and access to our concierge services.”
ENTITY RELATIONSHIP BUILDING
Link your property to verified entities that AI engines recognize and trust. This includes local landmarks, transportation hubs, cultural attractions and industry associations that provide context and authority signals. Develop content that naturally incorporates these relationships. “Located two blocks from the Portland Head Light and five minutes from the Eastern Promenade, The Grand Harbor Hotel provides easy access to Maine's most popular attractions.”
CONSISTENCY AND ACCURACY STANDARDS
AI engines validate information across multiple sources before including properties in recommendations. Inconsistent information (different phone numbers, contradictory policies, mismatched amenities) creates trust problems that may result in exclusion.
Maintain identical information across your website, Google Business Profile, OTA listings, review sites and social media profiles. Regular audits ensure accuracy and identify discrepancies that undermine AI confidence in your property information.
Measurement Revolution (KPIs for the Zero-Click Economy)
Hospitality has lived by a familiar chain of metrics. Search impressions and click-through rates from Google Search Console. Referral traffic and session data from Google Analytics. Conversion tracking through goals and ecommerce events, and source attribution showing whether bookings came from organic search, paid ads, social media or direct visits. These KPIs mapped a clear path. Travelers see your listing in search results, click through to your website, browse your content, and complete a booking.
This measurement framework works well when discovery happens through clickable channels. A traveler searches “hotels near Pike Place Market,” sees your property in Google results, clicks your organic listing, explores your amenity pages, and books. Google Analytics captures every step. The search query that brought them, pages they viewed, time spent on site, and the conversion event that completed their journey.
When travelers discover your hotel through AI conversations that never generate clicks, traditional analytics see nothing. The discovery, consideration and initial intent formation happen in environments completely invisible to Google Analytics, Search Console or any traditional tracking.
The rise of AI-driven discovery engines has disrupted this flow. In conversational search, there may be no impression, no click, and often no measurable referral source. Instead, the decision is being shaped within the AI environment itself before a guest ever reaches your website. Traditional KPIs measure what happens after discovery, while the real competition now takes place earlier and out of sight. Are you even part of the conversation when a traveler asks an AI where to stay?
Old funnel KPIs (impressions, clicks, conversions) measure behavior after exposure. These visibility KPIs (citation, share, placement, coverage, compset, accuracy) measure exposure inside AI answers, which is where zero-click discovery now happens.
The two sets aren’t mutually exclusive. Hotels still need conversion tracking, revenue attribution and channel mix reporting. But executives also need to understand that in a zero-click economy, the levers of demand shift upstream. If you don’t appear in the AI's answer, no amount of website optimization or channel strategy will matter because the guest never even knew you were an option.
This is why experimentation is essential. The industry hasn’t yet settled on a single standard, and AI engines are evolving too quickly for rigid formulas. Hotels must begin testing visibility across platforms, correlating those measures with branded search traffic, direct booking mix and revenue outcomes, while refining the approach quarter by quarter. The winners will be those who embrace this measurement revolution early, treating visibility as a core commercial KPI for the AI era.
These formulas represent the foundation of AI-era measurement. As the industry matures, expect refinements around query categorization (transactional vs. informational), seasonal weighting and market-specific benchmarks. The key is to begin tracking now, establishing baselines before your competitors recognize what is at stake. Define a fixed prompt bank by theme (family/luxury/budget), geography and trip intent. Run 150 or more prompts per engine per month.
THE VISIBILITY RECKONING
The hospitality industry stands at an inflection point that will define competitive dynamics for the next decade. While properties continue investing in traditional digital marketing based on 2019 playbooks, the fundamental mechanics of travel discovery have shifted.
This transformation reveals a sobering truth. The marketing metrics hospitality has relied on for 20 years now measure outcomes after the most critical decisions have already been made. By the time travelers reach your website, AI engines have already determined whether you exist in their consideration set. Your beautifully optimized landing pages, carefully crafted room descriptions, and sophisticated conversion tracking capture only the final moments of journeys that began in algorithmic conversations you can't see.
The measurement infrastructure that built modern hotel marketing (Google Analytics, Search Console, PPC dashboards) was designed for an economy where discovery happened through clicks. That economy is ending. The new economy operates through influence, mention and algorithmic inclusion in platforms that generate no referral traffic, create no attribution trails, and leave no measurement breadcrumbs for traditional analytics to follow.
When 60% of search queries end without clicks and the majority of travelers are using AI for planning, the window for gaining visibility into the new discovery economy is narrowing rapidly. Properties that begin AI visibility measurement now establish intelligence advantages that compound monthly. Those who wait face the exponentially more difficult challenge of competing against properties that understand market dynamics they can’t even see.
Measuring and optimizing across multiple AI platforms, query types and shifting answers is complex, but it is achievable. With clear playbooks, a focused toolset and a steady testing cadence, internal teams can build this capability. Even if you're starting from zero, you can stand up the essentials and expand as you learn. The aim is to add a modern visibility measurement function that evolves your current strategy and keeps you competitive in today’s discovery economy.
