Industry
SEO & AI Search Visibility for Hospitality
Hospitality SEO is a margin war. Every booking that comes through Expedia or an OTA costs 15-25% commission; every reservation through your own site keeps that margin. The OTAs outrank you for generic searches and even bid on your brand name — so the fight is won on brand-search dominance, local discovery, and the experience content OTAs can't replicate. And the ground is shifting: travelers now ask AI assistants to plan trips — "three days in the area, where should we eat, where should we stay" — and the engines answer with specific recommendations synthesized from reviews, local coverage, and how well your web presence describes what makes you worth choosing. Being recommendable to a machine that's read everything about your market is the new visibility problem.
What makes this industry different
- OTAs tax every booking they touchBooking.com and Expedia dominate generic accommodation searches with billion-dollar SEO operations and bid on your brand name besides. Beating them head-on for "hotels in [city]" is unrealistic; recovering the direct booking on brand searches, local queries, and experience-led discovery is where the commission math swings back your way.
- AI trip-planning answers are the new front door"Plan a weekend in Asbury Park" typed into ChatGPT returns specific hotels and restaurants with reasons — synthesized from reviews, local press, and structured data. Properties with a thin or generic web presence simply don't appear in the itinerary, no matter how good they are in person.
- Reviews are ranking, conversion, and AI input at onceGoogle, TripAdvisor, and Yelp signals drive local rankings and directly shape what AI assistants say when asked for the best spot in town. Volume, recency, and — underrated — the substance of owner responses all feed the machine. Reputation here isn't PR; it's infrastructure.
- Local discovery queries decide restaurant traffic"Best brunch near me," "date night restaurants [town]" — these resolve in the map pack and in AI answers, driven by review signals, category precision, photo freshness, and Business Profile activity. A restaurant's Google Business Profile is functionally its second website, and most are abandoned after setup.
- Seasonality punishes static sitesHospitality demand moves with seasons and events, but most venue sites are brochures that never change. Ranking for "[town] restaurant week," holiday bookings, or event-weekend searches requires content published on the demand calendar, months ahead of the spike.
How I approach it
- I lock down brand-search real estate first — your site, profiles, and knowledge panel dominating your own name — because losing a brand-name click to an OTA ad is pure margin bleed and the fastest thing to fix.
- I make direct booking findable and structurally legible: Hotel or Restaurant schema, price and amenity data, menu markup, and clean paths from every discovery surface to your booking engine instead of an OTA's.
- I run Google Business Profile as a channel, not a listing: weekly photo and post cadence, category and attribute precision, Q&A management — the operational habits that hold map-pack positions in competitive food-and-stay markets.
- I build the experience content OTAs can't write: neighborhood guides, seasonal itineraries, what-makes-this-place content — which ranks for discovery queries and gives AI trip-planners something specific to recommend you for.
- I test AI recommendations for your market directly — what assistants suggest for your category and town, who gets named, why — and close the gap with structured data and citable local coverage.
- I put review strategy on operations: systematic post-stay and post-visit asks plus substantive owner responses, feeding rankings, conversion, and AI answers simultaneously.
Frequently asked questions
Can a hotel realistically reduce OTA dependence through SEO?
Yes, though the goal is rebalancing, not elimination — OTAs still deliver discovery you'd struggle to replace. The realistic playbook wins brand searches outright, grows direct bookings on local and experience queries, and converts OTA-acquired guests to direct rebookers. Shifting even 15-20% of bookings direct materially changes property economics.
How do we show up when people ask ChatGPT where to eat or stay?
AI trip answers are synthesized from reviews, local press, and structured data — so the work is a strong review footprint, precise schema markup, and coverage in the local food-and-travel writing engines cite. Distinctive, specific positioning helps enormously: AI recommends places it can describe a reason to visit.
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