Industry · Hospitality

Be the hotel AI engines recommend when a traveler asks where to stay.

Hotel groups, independent hotels, serviced apartments and resorts. ZivRank measures which properties AI engines recommend on your guests' questions, then works to get yours into the answer, with your own website as the source.

Check my AI visibility → How we measure

Travelers now ask AI engines for a hotel the way they used to ask a friend: by neighborhood, by purpose, by budget. The answer names a few properties and often links to booking platforms. Being named with your own site as the source brings the guest closer to a direct booking.

What we bring to hotel

Built for how your buyers research

Questions by purpose and place

“Quiet hotel near the convention center”, “hotel with a meeting room for 40 people”: we measure the questions that match your properties, city by city.

Your website as the source

When an AI engine cites a booking platform instead of your site, the booking goes elsewhere. We track which sources are cited for your questions and work to get yours reused.

Consistent facts everywhere

Amenities, access, capacity, policies: engines cross-check sources. Identical facts on your site, your listings and directories make your property easier to recommend.

Buying questions

What your buyers ask AI engines

Examples of the questions we measure for hotel groups and independents. Your own list is built and validated with you before the first measurement.

“Quiet hotel near the convention center for a business trip”

“Hotel with a meeting room for 40 people downtown”

“Best boutique hotel in the historic district with parking”

“Family-friendly beachfront hotel with a pool”

“Where to stay for a trade show at the exhibition center”

“Hotel with a fine dining restaurant and spa for a weekend”

“Extended-stay hotel for a several-week work assignment”

“Accessible hotel downtown for guests with reduced mobility”

Sources

Where the answers come from

Hotel answers draw on booking platforms, review sites, travel guides, tourism boards, business listings and hotels' own websites. We measure which ones the engines reuse for your questions before choosing where to publish.

Proof, not promises

Measured before and after

Every program starts with a locked baseline measurement and is re-measured with the same protocol. You keep the raw answers, so every number in your report can be checked. See a measured case study →

The method, applied to hotel

From baseline to re-measurement

Measure

The buying questions of your market (50 from the Core plan upward), asked 5 times on each of 5 AI engines. You see where you are named, where you are only a source, and where you are absent.

Diagnose

Who is named instead of you, on which questions, and which sources the engines reuse. Plus a technical audit of what stops AI engines from reading your site.

Produce

Assets the engines can cite, placed on the sources they already trust in hotel. Reviewed by an expert before anything goes live.

Re-measure

The same protocol, replayed identically. A change only counts if it rises above the noise floor set before comparison.

FAQ · Hospitality

Frequently asked questions

Can an independent hotel compete with large chains in AI answers?

On specific questions, yes. A purpose, a neighborhood, a capacity: there are few credible answers, and a well-documented property can make the list.

Do you measure bookings that come from AI engines?

We measure what the engines answer and which sources they cite. Tracking bookings from those answers depends on your booking engine and analytics: we scope it with you at the start.

Do you work with a single property or a group?

Both. For a group, questions are measured per property and per city, then consolidated.

How is progress measured?

A locked baseline, then re-measurements with the same questions and engines. You receive the raw answers, and each change is compared against a noise floor set beforehand.