AI SEO for restaurants.
When your customers ask ChatGPT, Gemini or Perplexity who to go to, the answer names a handful of businesses. This page is how your restaurant becomes one of them — the exact queries, signals and pages that decide it.
That’s the whole game: being the name inside the answer.
What your customers are asking AI right now
Real query patterns for restaurants. Every one of these ends with an AI naming businesses — the only question is whose.
- “best [cuisine] restaurant near me”
- “restaurants open now [suburb]”
- “best date night restaurant [city]”
- “restaurant with vegan options near me”
- “is [restaurant name] worth it”
Why restaurants win or lose in AI answers
The shortlist is brutal
"Where should we eat" may produce a short list from many restaurants in the area. With limited space in a conversational answer, clear and verifiable information matters.
PDF menus lose to text menus
Engines can quote dishes, prices and dietary options from menus they can read. A designed PDF or photo may expose less usable text, while an HTML menu is easier to use for queries such as "best pad thai near me".
Reviews are now dish-level data
When reviews repeatedly mention a dish, engines may connect it to dish queries. Gently prompting guests to name what they ate can strengthen that association over time.
The exact signals that get a restaurant named
- 1Restaurant schema (the real schema.org type) with servesCuisine, priceRange, hours and reservation info
- 2Menu as HTML text with prices and dietary tags — the highest-value crawlable asset a restaurant has
- 3Google Business Profile AND Bing Places complete, with attributes and booking links
- 4Reviews that name dishes — ask guests to mention what they ordered
- 5Occasion signals in text: date night, groups, kids, private dining — each is a query family
The generic version of this list, with difficulty ratings, is in our 20-step guide — the list above is what it looks like for your trade specifically.
Question pages that win for restaurants
LLMs quote pages that answer one question plainly. These are the ones worth owning in your area:
- Your menu as a real page with prices — plus a dietary-options section in plain text
- "Best [signature dish] in [city]" — target the dish-specific query with first-party detail
- "Do you take walk-ins / where do we park / can you do groups?" — a page for common logistics questions
Restaurants ask us
How do restaurants get into ChatGPT recommendations?
Engines can shortlist restaurants using readable menus, complete listings, consistent details and dish-level review evidence. Cuisine, price range and dietary options can influence relevance, while reviews may influence selection.
Do delivery apps help or hurt AI visibility?
They're a double-edged sword: they can make dishes findable, but inside another platform and its margin. They are not a substitute for your own crawlable menu, which gives engines a first-party source they may cite.
PDF menu vs web menu — does it really matter?
It can. HTML menus are generally easier for engines to parse and quote for dish, price and dietary queries. Keep the designed PDF for print, and publish the same content as a real page.
We do this for other industries too
Ready to be tonight's answer?
The $200 audit tests your real customer queries across ChatGPT, Gemini and Perplexity, and hands you the fix list — use it with us or run it yourself.