Does AI recommend your brand? A 10-minute check.
Buyers ask ChatGPT which brand to choose. Most founders have never checked what it answers. Here is how to run the check yourself — and what each result means.
You do not need a tool or an agency to find out whether AI recommends you. You need ten minutes, the assistants your buyers use, and a short list of honest questions. The result is usually clarifying: most small brands discover they are absent from answers their competitors appear in — and absence, unlike a low ranking, is invisible until you look.
Ask the way buyers ask
Write down five to ten questions a real customer would ask before buying in your category: ‘best [category] for [need]’, ‘[your brand] vs [competitor]’, ‘is [category] worth it’, ‘[category] in [country or city]’. Run them in ChatGPT, in Perplexity, and in Google’s AI results. Run all three — each platform leans on different sources, so being present in one says little about the others.
Read the answer like an auditor
For every answer, note three things. First: are you named at all — and if so, named with a link, or only in passing? Second: who is named instead of you; that is your real competitive set in AI search, and it often differs from the one you track. Third: which sources the answer cites — those publications, directories, and pages are the places a mention would move you into the answer.
Check what the model believes about you
Then ask directly: ‘What do you know about [brand]?’ Models sometimes carry outdated or invented details — wrong founding facts, discontinued products, prices that never existed. The correction is not a complaint form; it is publishing specific, factual content the model can quote instead: a precise about page and a detailed FAQ beat vague copy every time.
Score it, then repeat monthly
A simple scale is enough: named and linked, named without a link, or absent — per question, per platform. Ten questions once a month gives you a trend line, and the trend is what matters; single answers vary from day to day.
What to do with the result
Absent everywhere: start with the foundations — our guides to Generative Engine Optimization and answer pages cover the first moves. Named but never linked: structured data and third-party mentions are usually the gap. Named with wrong facts: publish the correcting content this week; misinformation compounds quietly.
How FIB approaches it
This check is the manual version of what we run for clients across markets and languages, tied to the content and off-site work that changes the result. If you would rather see the audit done properly for your category, get in touch.
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