An independent AI visibility benchmark of 10 boutique Hudson Valley & Catskills hotels across Google AI Overview and ChatGPT — the engine that owns local data versus the one that doesn't. 24 prompts, 3 runs, 144 queries.
AI visibility for Hudson Valley & Catskills hotels is not one game — it's several. Google AI Overview and ChatGPT read almost entirely different sources, reward different signals, and crown different winners. There is no universal "AI SEO" play: the property that wins is the one that matches each engine's source diet — owning its Google Business Profile and listings for AI Overview, and earning reviews, community, and press for ChatGPT.
Finding: The two engines we tested share almost no sources. Google AI Overview anchors on its own Knowledge Graph / Maps entities (54 citations) and then aggregators like Tripadvisor and Expedia; ChatGPT reads Yelp, Reddit, and earned editorial (Vogue, Condé Nast Traveler, Hudson Valley Magazine). The source graphs barely overlap.
Insight: AI visibility is no longer one game. As the AI-search war escalates, each engine is hardening its own source graph, so the inputs that earn a recommendation differ by engine.
Implication: Winning requires an engine-specific strategy: own the Google Business Profile and listings for AI Overview; earn reviews, community, and press for ChatGPT.
Finding: Across 120 discovery, comparison, and occasion results, Mohonk Mountain House leads at 42% share of voice, followed by Emerson Resort & Spa (26%) and Wildflower Farms (20%). The field then compresses sharply: five properties cluster between 5% and 13%.
Insight: AI does not rank by brand size or ad spend — mid-pack properties with deep review histories out-surface several better-funded competitors with thinner data footprints.
Implication: Reputation depth (reviews, structured data) translates into AI recommendations more reliably than marketing spend or room count.
Finding: On ChatGPT the category is winner-take-all — the leader takes 58% of all answers. On Google AI Overview, grounded in the Maps reputation graph, the field is flatter and review-rich challengers are far more competitive: a representative mid-pack property reaches 53% of the leader on AI Overview versus just 23% on ChatGPT.
Insight: The Maps-grounded engine rewards earned reputation; the web-text engine rewards brand buzz.
Implication: For review-strong but lower-awareness properties, Google AI Overview is the bigger near-term opportunity.
Finding: Visibility is uneven across intent. Properties surface best on specific occasion and direct-brand queries and worst on broad "best hotels in…" discovery — the highest-volume searches — where a representative mid-pack property appears only about 1 in 9 times. Even on direct-brand questions, Google AI Overview triggers an answer only ~42% of the time versus ChatGPT's 100%.
Insight: Broad discovery is the category blind spot, and AI Overview's inconsistent triggering on brand queries is a structured-data and content-coverage gap.
Implication: The highest-stakes, highest-volume queries are exactly where most properties are least visible — and most fixable.
Finding: On direct property questions, the hotel's own website is the dominant cited source — but OTA citations (Expedia, Tripadvisor) come almost entirely from Google AI Overview, which pulls OTAs roughly 4× more often than ChatGPT (8 versus 2).
Insight: The "OTA hijack" of direct bookings is real, but it is concentrated in a single engine rather than spread across AI.
Implication: Structured rates and availability schema plus a strong Google Business Profile can reclaim the citation on AI Overview, where the leakage actually occurs.
Share of voice across organic discovery, comparison, and occasion prompts (Tiers 1–3, 120 results). The category's marketing heavyweights lead, but the field compresses fast — review depth, not brand size, separates the middle of the pack.
Properties can appear at the same raw rate on both engines, yet the competitive context could not be more different — and it favors the engine that owns local data.
of the category leader. On a flat, evenly-distributed field, a review-rich mid-pack property (8 mentions) trails only the leader (15). Earned review depth translates here.
of the category leader. The leader takes 58% of all ChatGPT answers — a winner-take-all field where brand buzz crowds out smaller players.
Visibility is uneven across intent. Properties do best where the query is specific — an occasion, or a brand by name — and worst in broad "best hotels in…" discovery, the highest-volume, highest-stakes searches.
| Prompt intent | Google AI Overview | ChatGPT | Read |
|---|---|---|---|
| Organic discovery (best resorts in…) | 10% | 13% | Blind spot |
| Competitor comparison | 7% | 13% | Thin |
| Occasion (weddings, winter, dining) | 27% | 13% | Strongest |
| Direct brand question | 42% | 100% | AIO gap |
The two engines share almost no sources. Google AI Overview anchors on its own Knowledge Graph / Maps entities first, then quotes aggregators; ChatGPT reads Yelp, Reddit, and editorial. As the AI-search war escalates, every engine is hardening its own source graph — so AI visibility is no longer one game, it's several.
Instagram25Independent research conducted on the AIVO platform; no hotel paid to be included or was notified prior to data collection.
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