GEO for Restaurants and Hotels: How to Reply to Reviews So ChatGPT Cites You

Your future guests no longer look for a table for dinner or a room for the weekend just by typing a few words into a traditional search box. More and more often they open apps like ChatGPT, Perplexity or Claude, or wait for the summary that Google generates right in search through Google AI Overviews (powered by Gemini). They type a long, specific request: "Rate the three best cafes in the city centre for a Sunday brunch that bake their own pastries and have room for a pram." You want your business to be the one that appears in that long answer. Welcome to the world of Generative Engine Optimization, or GEO for short.

Optimising content for generative models is a completely new discipline. If you want to win new guests, you cannot ignore the fact that large language models (LLMs) read your public data. And one of the richest sources of that data is your reviews and your replies to them.

The difference between traditional SEO, local SEO and GEO (AI SEO)

Let us look at the types of optimisation your business has available, because they often get mixed up.

Classic SEO focuses on site structure, backlinks and keywords. The goal is to get your website as high as possible in the list of blue links. If a guest searches for "hotel by the lake", you want to be on the first page.

Local SEO, specific to Google Maps or Apple Maps, deals with distance, relevance and the visibility of your Google Business Profile. The point is that when someone searches on their phone in a given area, your red pin shows up on the map together with your stars.

GEO (Generative Engine Optimization), also called AEO or LLMO, is not about blue links or pins. It focuses on making your business part of the direct text answer the model generates. Here the algorithms look for a clear match between facts and the user's request. They need unambiguous statements, backed by guest experiences, so they can confidently write: "According to reviews, this place is ideal for brunch because it serves homemade sourdough pastries."

Why do models read your reviews? RAG in practice

Artificial intelligence does not make information up out of thin air. It uses a process technically called Retrieval-Augmented Generation (RAG). In practice this means that when a user asks a question in Perplexity or in ChatGPT with web access, the model starts searching the internet in real time.

It does not only read the static texts on your website. Models actively scan portals such as Tripadvisor, Booking.com and your Google Business Profile to check whether your marketing claims match reality.

Reviews and your replies to them are one of the current sources an assistant finds and reads during this kind of search, and they directly build the context around your brand. If a customer praises a specific product in their review and you confirm and expand on that information in your reply, you create a clearly worded fact that the model can find and quote the next time someone asks a similar question.

Practical steps: how to reply with GEO in mind

Stop writing generic replies such as: "Thank you for your visit, we look forward to seeing you again." From a GEO point of view they are worthless. Models cannot extract anything useful about your hotel or restaurant from them. So how should you go about it?

1. Give precise facts and figures: If a guest praises their stay at your hotel, make the reply personal, but add context. Example: "We are very glad you slept well. We fully renovated our Deluxe rooms in 2023 and fitted them with soundproof windows so that the rooms are quiet at night." When a model reads this, it has a concrete fact on which to base a recommendation when someone asks for a "quiet hotel in the city centre".
2. Use the unique names of dishes and services: Generative search engines love specialities. If a guest mentions a dessert in their review, name it in your reply. "We are delighted you enjoyed our pistachio cake, which our pastry chef bakes fresh every day from 6 a.m."
3. Build frequent questions (FAQ) into your replies: Think about what guests ask most often. Perhaps prams, dogs or parking, or food intolerances. If there is room in the context of the reply, mention it. For example: "Thank you for the great rating. Next time feel free to bring your four-legged family member too, as our terrace is dog-friendly all year round."
4. Write quotable sentences: Language models look for so-called semantic density: a lot of information expressed in a clear and simple form. Write your replies systematically, clearly and with confidence. Avoid vague descriptions of fleeting feelings and make concrete, clear statements about what you do.

How to stay consistent with the Reputo platform

The biggest challenge when moving to GEO-optimised content is consistency. Writing a precisely worded reply to every review, full of facts, specific names and information, takes an enormous amount of time.

This is where the Reputo platform comes in. Reputo monitors new reviews on Google and, from the PRO plan, on Booking.com as well. For every new review it suggests a reply in your brand's tone and publishes it once you approve it. Before approving, you can edit the draft and add facts about your business, such as the name of a speciality, parking or a terrace where guests can bring their dog.

Reputo learns from the edits you make to replies and remembers the facts about your business that you add. Topic analysis of your reviews also shows you what guests mention most often and how this changes over time. These are exactly the topics worth confirming and expanding on in your replies.

So make sure your reputation and the data about you are ready for the new era of generative search. When your future guests ask ChatGPT for the ideal place for their dinner or holiday, let them find you before they find your competitors.

Reputo saves you time here: a draft reply in your brand's tone is ready for every new review, and you add the specific facts and approve it. The free plan for one location is enough to try it.

Try Reputo free on one location