Industry page template. Body copy is stubbed — replace with real aggregate audit data before publishing.
TemplateIndustries · Restaurants
When someone asks an AI assistant who to call in your category and your city, one company gets named. We measured what separates the companies that get named from the ones that do not.
What we found in this vertical
00%
of audited Restaurants sites had no discoverable pricing
00%
were never named for a high-intent prompt
0.0
average GEO readiness score in this vertical
00
sites in the sample — replace before publishing
Placeholder figures. Replace with aggregate results from real Restaurants audits, with sample size and date range.
Common findings
Stubbed copy for the template. Replace with the real finding rate and a short explanation of why AI assistants skip businesses whose costs it cannot summarise.
Maps to: GEO Readiness
Stubbed copy for the template. Replace with the observed pattern — a single services page that prevents a model from tying a specific job to your business.
Maps to: GEO Readiness
Stubbed copy for the template. Replace with the real data on how often the areas served are only visible in a footer or a map embed.
Maps to: AI Answer Share
Stubbed copy for the template. Replace with the comparison finding on content depth against the businesses AI names in this vertical.
Maps to: Competitive Analysis
The questions we test
These are the kinds of prompts we run against a live AI engine for a Restaurants audit. Yours are generated from your services and service area.
who should I call for restaurants in {city}
best restaurants company near {suburb}
how much does a restaurants service cost in {city}
which restaurants companies in {city} offer 24 hour service
is {business} a good restaurants company
Same audit, tuned to your trade
The three checks do not change. The prompts, competitor set and roadmap priorities do.
