AI visibility for restaurants in Columbus, OH
For restaurants and the agencies that market them · part of our AI visibility for restaurants industry guide
When someone in Columbus asks ChatGPT, Gemini or Perplexity for a restaurant recommendation, the assistant answers from the public data layer it can see: profiles, listings, reviews, and the words on your website. If that layer is thin or inconsistent, the answer names someone else — and the loss is invisible, because nobody tells you what the AI said.
FoundNow measures that layer. We ask the assistants the questions real buyers type, several times each, and report how often a business is mentioned as a rate with a 95% confidence interval — never a single-number claim. Every sample records which sources the assistant cited and which model version produced the answer.
What a report shows for a restaurant in Columbus
- Mention rate reported per engine, each as a rate with a 95% confidence interval
- The exact engines and model versions used are listed in the report itself
- The sources each assistant actually cited — profiles, directories, review sites, your own site
- The same measurement for one competitor, so the gap is concrete
- A fix list ordered by impact and effort: profile completeness, listings consistency, schema and on-site answers
Why monthly re-runs instead of a daily dashboard
Assistants produce a different answer every time they are asked, so daily spot checks mostly measure noise. Monthly re-runs with fixed questions turn sampling into a trend you can act on — and the method is documented in full on our methodology page.
Sample buyer questions we ask
Three examples from the restaurants question set (the full set is part of the product, not this page):
- “best brunch spots downtown”
- “family friendly restaurants near me”
- “best steakhouse in”
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