Most hospitality SEO programs start with keyword research. Most of that keyword research is wrong. The mistake isn't choosing the wrong tools — it's optimizing for the wrong half of the funnel. Hotels obsess over branded queries (their own name) and transactional queries ("hotels near Times Square") while ignoring the informational queries that travelers run weeks before they shortlist anywhere to stay. Those informational queries are where direct booking growth actually comes from, and they're where most hotels lose to OTAs and travel publications by default.
This post is the working framework I use on every new hospitality engagement. It's the version I wish someone had handed me five years ago. The framework is opinionated, hospitality-specific, and built to find the queries that produce bookings — not the queries that produce traffic dashboards.
The four query types every hotel needs to map.
Hospitality search behavior follows a predictable pattern that doesn't match general SEO assumptions. Travelers research, compare, shortlist, and book — and each of those stages produces a different query type with different competitive dynamics and different conversion math.
Type 1: Discovery queries.
These are the queries travelers run 2-12 weeks before they book anything. "Best things to do in Charleston in fall," "is Aspen worth visiting in shoulder season," "where to stay for a wedding in the Caribbean," "weekend trips from New York under $1000." Discovery queries don't include a hotel name. They don't include a brand. They often don't even include the word "hotel" or "resort." But they're where the entire travel decision starts.
Hotels almost never rank for these queries. The SERPs are dominated by Conde Nast Traveler, Travel + Leisure, AFAR, U.S. News, and increasingly by AI Overviews that pull from those publications. This is the biggest single opportunity in hospitality SEO — and the hardest one for hotels to compete for, because it requires publishing destination-quality content, not promotional content.
Type 2: Comparison and shortlist queries.
Once a traveler has chosen a destination, they shift to comparison. "Boutique hotels in Charleston," "best boutique resorts in Caribbean," "where to stay in Sonoma without a car," "family-friendly resorts in Hawaii under $500." These queries include intent qualifiers (boutique, family-friendly, under $X) and produce shorter shortlists.
Hotels compete with each other and with OTAs on these queries. Booking.com, Expedia, and Tripadvisor own the top organic positions for nearly all "boutique hotels in [destination]" queries. Hotels that publish thoughtful destination guides can break in — but it takes 6-12 months of consistent content production to displace the OTAs.
Type 3: Branded queries.
The traveler now knows your name. They search "[property name]," "[property name] reviews," "[property name] availability," "[property name] phone number." Branded queries are easy for hotels to rank for because Google understands the brand-property relationship. The fight here is against the OTAs bidding on your own brand name (Booking.com running paid ads on "Marriott Times Square") and against review sites cluttering your branded SERP.
Most hotel direct bookings come from branded queries. That's not because branded queries are where the value is — it's because that's the easiest part of the funnel to capture, and most hotels capture only that part.
Type 4: Transactional queries.
The traveler is ready to book. "Hotels in Charleston," "Asheville inn booking," "rooms in Napa Valley." Transactional queries are dominated by OTAs because OTAs spend hundreds of millions of dollars on these terms across Google Ads, organic SEO, and Maps. A single boutique hotel rarely outranks Booking.com for "hotels in Charleston." The smarter play is to skip transactional queries entirely and focus on the destination-specific niches OTAs underserve.
The framework: four phases of hospitality keyword research.
Phase 1: Define the property's true market geography.
Before you research a single keyword, define the geographic radius of your property's true market. This is rarely the same as your address.
A hotel in downtown Asheville has three different market geographies:
- Hyperlocal: within walking distance of the property (relevant for "best restaurants near [hotel]," "things to do near [hotel]")
- Destination: the city or region the property is in ("Asheville," "Blue Ridge Mountains")
- Catchment: the cities travelers come from to reach the destination (for Asheville: Atlanta, Charlotte, Raleigh, Knoxville)
Each geography produces different keywords. Hyperlocal keywords have small volume but high conversion. Destination keywords have larger volume but more competition. Catchment keywords (e.g., "weekend trips from Atlanta") have huge volume and lower competition, but require destination-specific content to rank.
Most hotels research only destination keywords. The other two geographies are where the openings are.
Phase 2: Map the traveler's question journey.
For each property type, write down the 30-50 questions a traveler asks before they book. Not keywords. Questions. The questions reveal the queries.
For a boutique resort in Sonoma:
- Is Sonoma good for couples?
- How does Sonoma compare to Napa?
- What's the best time of year to visit Sonoma?
- Do I need a car in Sonoma?
- Which boutique resorts in Sonoma have spas?
- What are the best wineries to visit by yourself?
- Where should I stay if I'm not into wine?
- How many days in Sonoma is enough?
- Is Sonoma kid-friendly?
- What's the weather in Sonoma in [month]?
Each question, once transformed into a search query, is a target. Together they form the topic graph the property needs to populate. This exercise alone — done thoroughly for 30-50 questions — produces a more accurate keyword list than three hours in Ahrefs.
Phase 3: Validate volume and intent with tools.
Now you bring in Ahrefs, Semrush, or Ubersuggest. For each question-turned-query from Phase 2, check:
- Monthly search volume — even 50-100 monthly searches is worth ranking for in hospitality, because the intent is high
- Keyword Difficulty (KD) — under 30 is achievable for new sites; 30-50 is medium-term; 50+ requires real authority
- SERP intent — what's currently ranking? Travel publications, OTAs, Google's own People Also Ask, or hotels?
- SERP features — does the query trigger an AI Overview, a featured snippet, a local pack, a knowledge panel?
The SERP intent check is the one most teams skip. If "boutique hotels in Sonoma" returns only OTAs and Booking.com, no amount of hotel content will displace them. But if "best things to do in Sonoma for couples" returns travel publications, a well-written destination guide from a hotel has a real shot.
Phase 4: Cluster, prioritize, schedule.
Once you have your validated keyword list (typically 200-400 queries for a single property), group them into topic clusters. Each cluster becomes a multi-post initiative on the property's content calendar.
For Sonoma, the clusters might be:
- Sonoma destination guides (10-15 posts)
- Boutique hotel comparison and category queries (5-8 posts)
- Wine country tactical content (8-12 posts)
- Couples / honeymoon content (4-6 posts)
- Catchment market content — Bay Area weekend trips (6-10 posts)
Prioritize clusters by a combination of volume × winnability. A cluster with 5,000 monthly searches and KD of 25 beats a cluster with 12,000 searches and KD of 55. Volume isn't the metric. Volume you can actually rank for is the metric.
The AI-search layer most teams miss.
The framework above is the traditional SEO version. In 2026, you need a second layer: AI-search-specific keyword research.
AI Overviews, ChatGPT, Claude, and Perplexity don't always show for the same queries Google ranks blue links for. The "AI-triggering" subset of your keyword list looks different. To find it:
- Take your top 50 highest-value queries from Phase 3
- Run each one in Google and check whether an AI Overview appears
- Run each one in ChatGPT, Claude, and Perplexity — record which sources get cited in the answer
- Note any queries that produce AI answers but where your property (or no hotel at all) is cited
The queries that produce AI answers and don't cite a hotel are the highest-leverage targets in 2026. The AI systems are still calibrating which sources they trust, and there's an open window for hotels to become the cited source. Once an AI system starts citing your property regularly, that citation persistence compounds for months.
What this framework will not do.
Keyword research isn't the whole job. It's the foundation. Several things this framework explicitly doesn't address:
- It won't tell you what content to write — that's the content brief phase, which comes after
- It won't tell you how long the content should be — that depends on the SERP intent and competing pages
- It won't tell you the technical fixes the site needs — that's a separate audit
- It won't replace judgment about your property's positioning — keywords reflect market demand, not strategic intent
Keyword research is the input to content strategy, not a substitute for it. A hotel with great keyword research and bad content production will not rank. A hotel with mediocre keyword research and excellent content production will rank for things its competitors don't even know to compete for.
If you want a competitive density analysis of your destination's SERP — which keywords are open, which are locked, where the AI-search openings are — that's part of every Digital Fox audit. Free, no commitment.