How to Check If AI Mentions Your Brand (Free AI Visibility Checker)

TL;DR: Open ChatGPT, Perplexity, and Gemini in fresh sessions, ask each one five to ten questions your real buyer would ask, and record four things per answer: whether you were mentioned, where you appeared, what reason the engine attached, and which sources it cited. Repeat monthly. It costs nothing, takes about fifteen minutes, and tells you your baseline — with real limits this post is honest about.

What's the fastest way to check if AI mentions your brand?

Ask the engines yourself, the way a buyer would. Open ChatGPT, Perplexity, and Gemini — free tiers are fine — and put the same questions to each one. Two rules make the result trustworthy:

• Use fresh sessions. ChatGPT's memory and custom instructions can skew answers toward brands you've discussed before. A clean session (or a logged-out/incognito window) gets you closer to what a stranger sees.
• Ask category questions, not just your brand name. "Tell me about [Brand]" only tests whether the model has heard of you. "What's the best [category] for [situation]" tests whether you get recommended — which is the question that moves revenue. Ask both; they diagnose different things, and knowing where you stand is the ground floor of Answer Engine Optimization.

Ask each question in all three engines, not just one. The same brand routinely gets different treatment across engines because each weighs sources differently — that spread is itself useful data about where your evidence gaps live.

Which prompts should you test?

Test the question shapes buyers actually use at the point of decision, in your buyer's words rather than your internal category jargon. Four shapes cover most of the decision:

1. Shortlist prompts — "best [category] for [specific situation]." The workhorse. Run two or three variants scoped to your actual customer segments.
2. Comparison prompts — "[you] vs [your main competitor]" and "[competitor] alternatives." These reveal whether you appear in head-to-heads you didn't know were happening.
3. Worth-it prompts — "is [your brand] worth it," "is [your brand] any good."
4. Trust prompts — "is [your brand] legit," and for anything involving money or data, "is [your brand] safe."

Five to ten prompts total is enough for a real signal. Write them down and reuse the identical list every time — the value compounds only if you're comparing like with like.

What exactly should you record?

For every prompt-engine pair, log four fields — plus the date. A plain spreadsheet with one row per prompt per engine is all this needs:

• Mentioned: yes or no. The binary that matters most.
• Position: were you the first brand named, one of several listed, or mentioned only in passing? First-named and list-padding are very different outcomes that a yes/no check flattens.
• Sentiment and reason: did the engine attach a justification ("known for X," "good for Y") or a hedge ("some users report...")? A mention with no reason means you're filler in someone else's answer. Copy the actual sentence — you'll want the wording later.
• Citations: which sources the engine leaned on. Perplexity and Gemini show them directly; for ChatGPT, ask "what sources is that based on?" The cited domains are the most actionable field in the whole log, because they tell you exactly where the answer is being decided.

Date matters because answers drift. Six months of dated rows turns anecdotes into a trend line.

How often should you re-check?

Monthly, at minimum, with the same prompt list — and immediately after anything that should have moved the needle: a launch, meaningful press, a burst of reviews, or a site restructure. AI answers shift as models retrain and re-crawl the sources they trust, so a brand cited today can quietly drop out weeks later without anything visibly breaking on your side. A monthly cadence catches the drift while it's still one month old.

Is there a free AI visibility checker?

Yes — and it's the fastest route once you've outgrown checking by hand. A free AI visibility checker asks the major engines the questions your customers ask and reports whether you're named, where a competitor wins instead, and what's blocking you. You can approximate it manually with the method above, but a checker runs it across ChatGPT, Perplexity, and Google's AI surfaces in minutes and returns a ranked fix list — ClappX's free scan does exactly this before any payment.

What are the limits of manual checking?

Be honest about what a hand-run check can and can't tell you, because over-reading a single session is the most common mistake:

• It's a snapshot. You learn where you stand today, not whether last month's work moved anything — unless you've kept the dated log religiously.
• Answers vary run to run. The same prompt can produce different brand lists in two consecutive sessions. Treat any single answer as a sample, not a verdict; if a result surprises you, run it two or three more times before acting on it.
• Your prompt list is tiny. Ten prompts stand in for the thousands of phrasings real buyers use. A competitor can own variants you never test.
• You're blind between checks. If an engine drops you or a new hedge appears mid-month, you find out at the next check — or when the pipeline dips.

None of that makes the manual check not worth doing — it's the right first move, and it's free. When the results come back and you want to act on them: if you're absent from the answers entirely, start with the five causes of AI invisibility to find out why. And when you're ready to go past the quick check, the full 5-minute AI visibility audit covers how to interpret each outcome and what to fix first for each.

The limits above are also, honestly, the case for automating the loop once you've run it by hand a few times: a continuous scan like ClappX AnswerX runs the same prompts across engines on a schedule, keeps the log for you, and flags the week an answer changes instead of leaving it for month-end.