What guests really ask the AI: an analysis of typical restaurant prompts

Why guests now ask the AI instead of Google

Search behavior has shifted. Whoever used to type "Italian dinner downtown" into Google and click through ten links now phrases a full sentence in ChatGPT: "I'm looking for a cozy Italian restaurant for four people, one of them vegetarian, for Saturday evening around 7 p.m." The AI doesn't deliver a list of links but a finished recommendation with two or three concrete names. For you as a restaurateur that means: there's no more clicking through and no second chance on page two. Either your restaurant is in the answer, or it simply doesn't exist for that guest.

This development hits the restaurant industry harder than many others. Eating out is a spontaneous, context-dependent decision: time of day, occasion, group size, diet, price expectation. The AI processes exactly such combinations in a single sentence, and this is precisely where it's decided whether your place makes it into the result. Anyone who understands what these questions look like and which data the AI draws on to answer can help things along deliberately. The first step is therefore to take an honest look at the typical guest questions at all, instead of ignoring them.

Important to know: the AI doesn't invent its recommendations. It pulls them together from Google Business Profiles, review portals, menus, industry directories and your own website. Your visibility in the AI is therefore not chance, but the result of the traces your restaurant leaves online. Generative Engine Optimization, GEO for short, is the work on exactly these traces.

The most common restaurant prompts at a glance

When you analyze how people actually ask about restaurants, clear patterns emerge. By far the most common type is the local search with an occasion: "Where can I have a nice dinner for two in Rosenheim?" or "Recommend me a restaurant for a birthday with ten people nearby." These questions combine place, number of people and mood. The AI only answers with your name if it finds exactly these attributes for your place: location, capacity and the information that groups are welcome.

The second big block is diet and nutrition questions: "Which restaurant has good vegan options?", "Where do I get gluten-free pizza?", "Is there a place here with lactose-free cuisine?" Such prompts are increasing sharply, because this is where the AI plays to its real strength: filtering by details that were tedious in classic search engines. But if your menu doesn't contain these terms at all, no AI in the world can suggest you, even if your kitchen actually cooks vegan-friendly.

On top of that come practical logistics questions: "Which restaurant nearby is open on Sundays?", "Where can I eat spontaneously without a reservation?", "Is there a place with a terrace and high chairs for kids?" Opening hours, reservability, outdoor area, accessibility, parking, all of these are facts that are either cleanly recorded or simply missing. Missing facts are rarely guessed by the AI, they're simply left out.

What the AI really reads out of your data

A language model doesn't read your website like a person delighting in beautiful food photos. It searches for machine-readable facts: cuisine style, price level, opening hours, address, reservation option, special features. If this information only sits in an image of the menu or is hidden in a PDF, it practically doesn't exist for the AI. Text that's present as text and clearly labeled beats even the most beautiful design. That's the uncomfortable core of GEO for restaurants.

Especially underrated is the language of your guests. The AI matches wording: when people ask for "romantic", "quiet", "family-friendly" or "hearty home cooking", the model searches for exactly these words in your texts and above all in your reviews. A restaurant whose guests repeatedly write "cozy atmosphere" and "attentive service" in reviews gets favored for the corresponding prompts. Reviews are therefore not a side stage, but one of the most important data sources for your AI visibility.

Consistency counts too. If your restaurant is called "Ristorante" on Google, "Trattoria" on Facebook and "Restaurant & Bar" on your own website, if the opening hours differ in three places, the AI becomes uncertain. Contradictory data leads the model to name your place less often or not at all, because it doesn't trust the information. A uniform presence across all platforms is therefore unspectacular but effective.

Concrete example prompts and what they reveal about you

Take the prompt: "I'm in town on business and looking for a quiet restaurant for a lunch meeting." For your place to appear here, the AI has to recognize that you're open at lunch, that the atmosphere is rather quiet, and that solo guests or small business groups are well taken care of. If your page only says "We look forward to your visit", every one of these cues is missing. If, on the other hand, you write concretely "quiet lunch tables, WiFi, ideal for business meals", you give the AI exactly the building blocks it's looking for.

Or the classic: "Where can I get a good schnitzel nearby?" That sounds banal, but it's instructive. The AI needs the concrete naming of the dish. If your menu is online and "Wiener Schnitzel from veal" appears there, you're in the best position. If your menu is only a photo or not online at all, you'll practically never be named for this question, even though your schnitzel might be the best in town. Visibility comes from named facts, not from quality alone.

A final example: "Recommend me a restaurant with vegan options and a terrace for Friday evening." Here the AI has to satisfy three filters at once. Restaurants that cleanly list these features win such multi-condition inquiries almost automatically, because the competition fails on exactly one missing detail. The more precise your recorded attributes, the more of these combined questions the AI answers with your name.

Reviews: your most important raw material for the AI

No other signal weighs as heavily in the restaurant business as reviews. Language models treat reviews as a collective opinion and filter out of them properties you don't actively communicate yourself. If your guests often write about "large portions", "fair prices" or "lovingly done decor", then you show up for questions about exactly these aspects. Your job isn't to fake reviews, but to actively ask satisfied guests for honest, concrete reviews, ideally naming what they liked.

Your responses to reviews are visible too. When you react to criticism factually and kindly and respond gratefully to praise, an image of reliability emerges that the AI reads along. A restaurant that snaps back at every other negative review sends a different signal than one that stays composed. Feel free to ask your guests specifically to mention details: which dish, which occasion, which atmosphere. Exactly these details are the search terms of tomorrow.

Think of your menu as an AI document

The online menu is your restaurant's most valuable single document for the AI. Yet many restaurateurs hide it in a PDF, in an image or on a third-party platform without real text. For humans that may suffice, for language models it's a locked door. Make sure your menu is on your website as real, readable text, with clear dish names, short descriptions and labels like vegetarian, vegan, gluten-free or spicy. Each of these labels is a hit for a possible guest question.

Describe dishes the way guests would search for them. Instead of just "Pasta No. 4", write "homemade tagliatelle with porcini mushrooms, vegetarian". That way you cover several prompts at once: pasta, homemade, vegetarian, porcini. Add regional and seasonal hints where they apply, because "regional" and "seasonal" are frequent filter terms. A well-structured, honestly labeled menu is the cheapest and most effective GEO measure you can implement right away.

Keep the menu up to date. Nothing irritates the AI more than dishes that no longer exist, or prices from the day before yesterday. If you change seasonally, maintain the changes online too. An outdated menu leads to wrong recommendations, disappointed guests and in the end worse reviews, a cycle that turns directly against your visibility.

Maintaining your Google Business Profile and directories

Alongside your website, the Google Business Profile is the central source AI systems draw facts about your restaurant from. Opening hours, cuisine category, price level, attributes like terrace, wheelchair accessibility, reservability, takeout: fill in every field your profile offers. Many restaurateurs leave half of it empty and wonder why they don't show up for specific questions. Every filled-in attribute is a potential answer to a guest question that otherwise passes you by.

Pay special attention to special opening hours on holidays and to current photos. A model asked on a holiday about open restaurants favors profiles with well-maintained holiday information. Also take care of consistency across further directories, such as review portals and reservation platforms. Everywhere, name, address and phone number should be identical. This agreement, called NAP consistency in the jargon, noticeably increases the AI's trust in your data.

A simple roadmap for more AI visibility

Start small and concrete. Step one: put your full menu on your website as real text, including diet labels. Step two: complete your Google Business Profile with all attributes and current opening hours. Step three: over the coming weeks, deliberately ask satisfied guests for concrete reviews. Even these three measures measurably change how often your place appears in AI answers, and apart from time they cost you almost nothing.

After that, a test run is worthwhile. Open ChatGPT, Gemini and Perplexity yourself and ask the questions your guests would ask: about your cuisine, your location, your occasion. Are you named? Is the information correct? Wherever you're missing or shown wrongly, you've found your concrete to-do item. You should repeat this self-check every few months, because the models and their data sources change constantly.

GEO isn't a one-off project but a habit. Whoever maintains their data cleanly, up to date and in the language of their guests gets recommended by the AI more reliably than the neighbor who relies on good food alone. In a world where more and more reservations begin with an AI question, that's exactly the difference between a full and a half-empty dining room.