AI search for restaurant and hotel groups: one agency or site by site?
Updated By Akkrev
See how hotel and restaurant groups can improve AI discovery by location, assign the work and measure reservations and bookings per venue.
Key points
- Run AI search centrally. One owner keeps facts, tracking and fixes consistent across every venue.
- AI recommends venues, not brands. Each site needs its own page, listings and reviews to get named.
- The usual group problems are mixed-up facts between sites and only the flagship getting named.
- Track the same guest questions for each location, because results differ by city and neighbourhood.
- Local managers still matter. Reviews, photos and menu changes are best handled on site.
Central team
Owns venue facts, listings, tracking, location pages and the monthly report.
Each venue
Replies to reviews, updates photos and menus, flags changes to hours or events.
Website
One page per location with address, hours, menu as text and booking link.
Listings
Google, Apple Maps, Bing, Yelp, TripAdvisor and booking platforms kept identical.
Start with the locations that have capacity to take more bookings or covers. Give one person ownership of tracking and website changes. Ask each venue manager to keep local details current. Compare the same locations over time so the flagship’s results don’t hide a quieter venue’s gaps.
See what Akkrev offers hospitality groups, including how to scope a rollout and request pricing for three or more venues.
Why groups need a different approach
Guests ask ChatGPT for “a steakhouse near Liverpool Street” or “brunch in Manchester for six”. AI answers with a short list of venues, not brands. Uberall’s 2026 benchmark found AI assistants usually name only 3 to 5 restaurants per question. Your brand might be famous, yet a specific site still has to earn its place in that list.
Groups also start with an advantage. A known name, press coverage and many reviews give AI more to work with than a single independent has. The task is to make that strength reach every location, not only the busiest one.
Common problems in groups
- Facts get mixed up. AI quotes one site’s opening hours or menu for another.
- Only the flagship gets named. It has the reviews and press, while newer sites have little written about them.
- Location pages are thin. A shared template with a different address gives AI nothing to tell venues apart.
- Listings drift. A site changes its hours on Google but not on Yelp, TripAdvisor or the booking platform.
- Nobody measures by site. Brand-level checks hide the fact that some venues never appear.
What good looks like
Two well-known groups show the basics clearly. Dishoom gives each restaurant its own page with a map, menus and reservations, and publishes an llms.txt file that lists every location for AI assistants. Hawksmoor does the same across London, Manchester, Liverpool, Edinburgh and its US sites in New York, Chicago and Boston. Each location is a separate page with its own address.
That structure matters because AI needs a clear answer to “which Hawksmoor is in Manchester and when is it open”. A single page listing twelve addresses makes that hard.
Who does AI search for hospitality groups
| Provider type | Examples | Good for |
|---|---|---|
| Listing platforms | Yext, Uberall, SOCi | Keeping hours, addresses and menus identical across many directories |
| Local tracking tools | Local Falcon | Seeing where each site appears on maps and in Google’s AI |
| Hospitality agencies | Hotel and restaurant SEO agencies | Content, PR and website work done for you |
| AI visibility tools | Akkrev | Asking ChatGPT, Gemini, Claude and Grok your guest questions every week and showing who gets named |
Large chains often use a listings platform and a tracking tool together. Groups with three to fifteen venues usually need less. Clean listings, one good page per site and weekly tracking of the questions that matter cover most of it.
One agency or site by site?
Run it centrally. One owner can:
- keep a single source of truth for every venue’s facts,
- track the same questions for each location and compare results,
- spot when one site drops out and find the reason,
- make website changes once instead of twelve times.
Site managers still have a job. Guests write reviews about the venue they visited, and photos and menus change locally. Give each manager a short monthly list: reply to reviews, update photos, report any change to hours, events or menus.
What to track for each location
Pick 5 to 10 guest questions per site and keep them fixed. Mix general and specific questions, for example “best steak in Manchester” and “steakhouse near Deansgate with a private dining room”. Record which venues get named, which sources AI cites and whether the facts are right. Local Falcon found that the top 10% of restaurants take 74.5% of all visibility in Google’s AI, so small gaps between sites tend to grow.
How to grow bookings across multiple locations
- Pick the locations and times you want to fill. Compare midweek room nights or weekday dinner covers with the same days in a previous period. Note local events and changes in opening hours or prices.
- Check where each venue is losing the guest. Ask the same kind of question for each location. Save which venues are named, which pages are cited and which booking link appears. Follow that link on a phone.
- Give each manager one fix to own. One site might need a current menu, while another needs its booking link corrected. Check the live page after the update.
- Review the numbers by venue. Keep AI mentions and website actions separate from confirmed bookings, covers and revenue. See how to measure AI search results.
How Akkrev works with groups
Each plan covers one venue and tracks its guest questions weekly across four AI model families. For three or more venues we agree a group price. Book a call to talk it through, or see the standard plans.
Questions
Should a restaurant group hire one AI search agency or handle it site by site?
One owner for the whole group works better. Facts, tracking and website changes stay consistent, and you can compare venues on the same questions. Site teams keep doing reviews, photos and menu updates.
Who does AI search optimisation for hospitality groups?
Four kinds of provider: listing platforms such as Yext, Uberall and SOCi, local tracking tools such as Local Falcon, hospitality SEO agencies, and AI visibility tools such as Akkrev. Many groups combine a listings platform with a tracking tool.
Why does AI only recommend our flagship restaurant?
The flagship usually has the most reviews, press and links. Other sites often share one thin page. Give each venue its own page and listings, then track it on its own questions.
What does an AI search audit cost for a multi-venue group?
It depends on the number of venues and questions. Akkrev plans cover one venue each. For three or more venues, book a call for a group price.