Does AI recommend your venue?
Type any Mexico City restaurant, bar, cafe, or hotel. We ask AI assistants the questions your diners and guests actually ask — live, right now — and score how visible you are in the answers.
Frequently asked questions
How is this different from just asking ChatGPT about my venue?
ChatGPT will give you a friendly-sounding score on the spot, but it's a one-shot opinion — ask the same question twice and you'll get two different answers, and it often invents review counts or star ratings it can't verify. DiscoverCDMX runs a repeatable test: we ask two frontier models the exact same set of diner and traveler questions for your neighborhood, record which venues they name and in what order, and re-run the test so you can measure real progress.
Is this a real scan or a simulation?
Real. Every score comes from live model answers captured during your scan, plus a live fetch of your website. If a model doesn't respond, we exclude it from your score and say so on the report instead of filling in a number.
Why did ChatGPT give my restaurant a higher score than DiscoverCDMX?
ChatGPT grades generously and blends together things it can't measure — it assumes that if Google indexes your page, AI must recommend you. DiscoverCDMX measures the harder, honest question: when a real diner asks AI for a restaurant in Roma Norte or Condesa, does AI actually name you? A lower DiscoverCDMX score usually means indexing is fine but AI isn't recommending you yet — the exact gap diners feel.
What does each part of the score mean?
Recommendation = will AI name you when someone asks 'best restaurant in [neighborhood]?' Prominence = when named, are you #1 or buried at #5? Informational = will AI name you on occasion and intent questions (date night, brunch, mezcal, business dinner)? Content depth = does your website actually give AI something to cite (menu, hours, story, reservations, structured data)? All four roll into your overall grade.
What's in the free Visibility Snapshot versus the paid GEO Visibility Audit?
The Snapshot is the free one-page diagnosis: your score and grade, your score by AI model, three findings explaining why the score is what it is, five example questions with hit or miss, and your top competitor. The Audit is the paid document, built from the same scan: every question tested with each model's verbatim answer, the citation sources AI pulls from in your category, the full competitor teardown, entity and schema gaps, technical GEO analysis with a fix list, revenue-weighted priorities, and a sequenced 90-day roadmap. Two documents, one scan — the Snapshot is what AI thinks of you, the Audit is what to do about it.
Do I need to do anything after I sign up?
Either a quick onboarding call or a simple checklist. After that, we do the work — building your canonical DiscoverCDMX profile, answering the losing queries, and getting you into the neighborhood and occasion guides AI engines cite.
How quickly will I see results?
Most venues see visibility changes within the first 30–60 days. AI platforms update as your citations improve, and it compounds monthly as we ship new guides and Q&A pages that reference you.
What if I already rank well on Google or Instagram?
Great — but AI answer engines don't use Google rankings or Instagram at all. Being on page 1 of Google or having 40k followers doesn't mean ChatGPT recommends you when a traveler asks for a Roma Norte cocktail bar. Different algorithms, different strategy.
Does this only cover restaurants?
No — DiscoverCDMX runs visibility checks for restaurants, bars, cocktail bars, cafés, bakeries, hotels, rooftops, and experiences across Mexico City. The occasion questions we test are tailored to your category.
We confirm your venue and its category against Google's live place data, then ask frontier AI models — GPT-5.6, Gemini 3.1 Pro, and a live-web engine that answers with real citations — the everyday questions CDMX diners, cocktail crowds, and travelers actually ask. We record which venues each model names and in what order, fetch every source the models cite and check whether it exists and whether it mentions you, crawl up to ten pages of your own site for the signals engines need, and score recommendation, prominence, occasion coverage, citation presence, and site readiness from that evidence. Every scan is kept, so each re-run shows movement against your last one and against other venues in your category and neighborhood. Nothing is simulated: if a model doesn't respond, we exclude it and tell you. Results reflect each model's current knowledge and are educational, not a guarantee of ranking.