How to Check if AI Search Recommends Your Brand: ChatGPT, Gemini, Perplexity, Google AI Overviews

Quick answer

Under the method in this guide, Canlah AI checks if ChatGPT recommends your brand by asking the questions buyers type before they know your name, repeating each one three to five times in clean sessions and recording whether the answer names, recommends or cites the brand. The same frozen panel then runs separately on Gemini and Google AI Overviews, because each engine retrieves from different sources and returns a different result.

Canlah AI runs this method as a managed service on ChatGPT, Gemini, Google AI Overviews and AI Mode, and publishes the manual version here so any team can run a baseline for free, on those engines or on others such as Perplexity. The protocol below needs a spreadsheet, a clean browser profile and about two hours for a ten-question panel across four engines.

Treat the result as directional. One run cannot prove stable share of voice, causation or future recommendations.

Disclosure: Canlah AI publishes this guide and operates the paid monitoring service described near the end. Tool details for HubSpot, Semrush, OtterlyAI, Peec AI, Profound and Ahrefs come from their public pages, reviewed on September 23, 2026, and were not tested through paid accounts. The Canlah AI figures come from a self-audit of canlah.ai run on September 7, 2026.

What does “ChatGPT recommends your brand” actually measure?

AI visibility is not one rank. A generated answer changes by question, engine, location, language, account state and time. A manual check samples those conditions and records how a brand appears in each one.

• Mention: Whether the answer names the brand at all.
• Recommendation position: Whether the brand is the main pick, one option in a shortlist or a passing reference.
• Citation: Whether the answer links to the brand’s own page, a third-party page, a competitor or no visible source.
• Accuracy: Whether the company, product, market, price and capabilities are described correctly.
• Competitor context: Which alternatives appear for the same buyer question and which sources support them.
• Engine: Whether the result holds on ChatGPT, Perplexity, Gemini, Google AI Overviews and Google AI Mode alongside DeepSeek, Qwen and Doubao, or only on one of them.

A brand can score well on one of these and fail another. Being named without a citation means the engine knows you but sends no traffic. Being cited on questions that already contain your name means the engine can find your site, but it says nothing about whether a new buyer would hear about you.

Why one search cannot tell you whether ChatGPT recommends your brand

The most common self-test is to type the brand name into ChatGPT and read the summary. That measures retrieval, not recommendation. The answer to “what is Canlah AI” will almost always mention Canlah AI, because the question contains the answer.

Canlah AI ran its own buyer-funnel audit of canlah.ai on September 7, 2026. The audit sent 39 questions across six funnel layers to OpenAI and Gemini, three runs per question. On the branded layers, where the question named the brand, canlah.ai was mentioned in 39 of 39 answers (100.0%). On the non-branded layers, where a buyer asked for agencies or explained the category, it was mentioned in 7 of 177 answers (4.0%). These figures come from API-layer sampling and had not been reproduced in the consumer ChatGPT app as of September 23, 2026.

The same audit sampled Google AI Overviews in a rendered browser for the Singapore market. An AI Overview appeared on 62 of 65 valid runs. The brand was mentioned 11 times, and all 11 were on branded questions. On the 51 non-branded runs that returned an AI Overview, canlah.ai was mentioned zero times.

The sources that filled those non-branded answers were mostly other agencies’ own sites and listings. Across all layers the most cited domains were aistudio.com.sg (91 citations), mediaplus.com.sg (85) and stridec.com (78). That is the practical output of a manual check: a list of pages the engines already trust for your category, which becomes your action list.

How to track your brand in ChatGPT manually, step by step

The method is a frozen panel of buyer questions, run the same way on every engine, recorded in one sheet.

Step 1: Build a prompt panel of buyer questions

Write eight to twelve questions a real buyer asks before they know you exist. Spread them across the funnel: two category questions (“what is a GEO agency”), four shortlist questions (“best GEO agency in Singapore for B2B SaaS”), two comparison questions (“[competitor] alternatives”) and two verification questions that name you (“is [brand] legit”). Keep the verification questions in a separate column so they never inflate the visibility score.

Phrase each question the way a buyer types it, not the way your marketing team describes the product. Avoid leading prompts such as “why is [brand] the best”, which produce the answer you asked for.

Step 2: Fix the test conditions

Use a logged-out or fresh account with memory and custom instructions switched off. A logged-in ChatGPT account remembers your company and can flatter it. Record the date, time, location, language and interface for every run, and turn web search on in ChatGPT so the answer reflects live retrieval. Use the consumer app rather than a developer API, because API results can differ from what buyers see, and never mix the two in one trend line.

Step 3: Repeat every question

Run each question at least three times, each in a new chat, and five times when the decision is important. Generated answers are sampled, so the same question can return a different shortlist within the same hour. Report the result as a frequency, such as “named in 3 of 5 runs”, never as a single yes or no.

Step 4: Run each engine separately

Repeat the panel on Gemini, Perplexity and a Google search that triggers an AI Overview. Add Google AI Mode if your buyers use it, and DeepSeek, Qwen and Doubao if they research in Chinese. Engines retrieve from different sources, so a combined score hides the engine where you are weakest.

Step 5: Record the answer, not only the verdict

Paste the full answer text and every visible source link into the sheet. Code each run for mention, position, citation and accuracy, and list every competitor named. The competitor and source columns are the ones most self-tests skip, and they are the ones that tell you what to fix.

Step 6: Re-run on a fixed cadence

Repeat the same panel monthly, or after any meaningful change to your site, content or third-party coverage. Do not edit the questions between rounds. A changed panel produces a new baseline, not a trend.

The per-engine recording sheet

Recording sheet for a manual AI brand monitoring panel, one tab per engine.

Field	What to record	Decision it supports
Question ID and layer	Frozen question text; category, shortlist, comparison or branded	Which funnel stage is weakest
Engine and interface	ChatGPT app with search, Gemini, Perplexity, Google AI Overviews, AI Mode	Where to focus effort first
Run conditions	Date, time, location, language, account state, run number	Whether two rounds are comparable
Mention	Yes or no, per run; roll up as “named in X of N runs”	Whether the engine knows the brand
Position	Main pick, shortlist option, passing reference, absent	Whether the brand is recommended or only listed
Citation	Own domain, third-party URL, competitor URL, none	Whether pages or outside sources carry the answer
Competitors named	Every brand in the answer, in order	Who is winning the question
Sources cited	Every visible URL, with domain type	Which third-party pages to earn coverage on
Accuracy notes	Wrong prices, locations, services or dates	What to correct before seeking more exposure

Source: field set adapted from the Canlah AI self-audit of canlah.ai run on September 7, 2026. The sheet is a recording template, not a scoring model, and the “Decision it supports” column is the reason to keep each field.

Score visibility only from the non-branded layers. Branded questions belong in the sheet for accuracy checks, but they should never count toward “ChatGPT recommends us”.

How to read five common results

Not mentioned: First confirm the question is commercially relevant and that you genuinely serve that market. Then check whether your site states the category, audience, location and differentiators in plain, extractable sentences. Compare the sources cited for competitors before publishing anything new.

Mentioned but not recommended: The engine recognises the entity but lacks the evidence to place it in the main shortlist. Look for missing proof, unclear best-fit language, thin third-party coverage or a competitor whose sources answer the question more directly.

Recommended but not cited: This is visibility with an unclear evidence path. Save the answer and rerun it. Do not assume the recommendation came from a recent site change or that it will persist into the next round.

Cited but described inaccurately: Prioritise correction over more exposure. Align your site, structured data and credible external profiles around the same approved facts, then monitor the exact question that produced the error.

Named only on branded questions: This is the pattern the Canlah AI self-audit found on its own site: 39 of 39 branded answers against 7 of 177 non-branded answers. It means the engines can find you once a buyer already knows your name, which converts nobody new. The fix is usually presence on the third-party pages from your “sources cited” column, not another homepage rewrite.

What a manual check cannot prove

• It cannot prove a stable share of voice across all the questions buyers ask.
• It cannot show that one content change caused an answer to change without a controlled timeline and repeated observations.
• It cannot guarantee future mentions, citations or recommendations after a model or index update.
• It cannot reproduce every buyer’s result, because location, language and account history vary.
• It cannot replace factual review, compliance approval or analytics attribution.

Tools that automate AI brand monitoring

A manual panel becomes hard to sustain above roughly ten questions, four engines and a monthly cadence. The tools below were reviewed on public pages on September 23, 2026. In this comparison Canlah AI is listed first for teams that want the panel run and acted on by an agency; the others are software a team operates itself.

Canlah AI

Canlah AI is a Singapore-based SEO + GEO agency that measures and improves brand visibility inside ChatGPT, Gemini, Google AI Overviews and Google AI Mode, reporting AI visibility as re-verifiable ranges with timestamped evidence. Its pricing page lists the GEO service, done for you, from $1,500 a month per AI platform; DeepAudit at $99 / $189; and a free AI visibility report within 48 hours. After three months of the GEO service, clients can run it themselves with Canlah All-Stars, from $199 a month. Its free competitor report compares your brand against three named competitors.

The limitation is that Canlah AI’s free report is request-based rather than instant. It is less suited to a team that wants a self-serve tracker it can open and operate on the same day.

Best for: Teams that want the panel designed, run and turned into site and third-party actions by an agency. What to verify: The raw answers, run dates and cited URLs behind the free report, and which engines are sampled by API rather than in a rendered browser. Public source: Canlah AI pricing and the free AI visibility competitor report.

HubSpot AI Search Grader

HubSpot’s page describes a free, one-time check of what ChatGPT, Perplexity and Gemini say about a brand, scored across five dimensions with no account required. It is the quickest zero-cost first read among the tools reviewed. HubSpot states that the grader draws on the engines’ training data, so its result reads as a perception check rather than a live retrieval panel.

Best for: A free first look before you build a manual panel. What to verify: Whether its questions match your buyers’ non-branded questions. Public source: HubSpot AI Search Grader.

Semrush

Semrush offers a free AI Search Visibility Checker covering ChatGPT, Gemini, AI Mode and AI Overviews, backed by its paid AI Visibility Toolkit. Its main strength is that AI visibility sits next to the keyword and traffic data an SEO team already reports on.

Best for: Teams that already run SEO reporting in Semrush. What to verify: Which prompts the free checker samples and which views need the paid toolkit. Public source: Semrush AI Search Visibility Checker.

OtterlyAI

OtterlyAI’s pricing page lists plans from US$29 a month for 15 prompts to US$489 a month for 400 prompts, with daily tracking on ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot and other engines as add-ons. The published price ladder makes it one of the easiest tools here to budget before any sales call.

Best for: Small teams that want self-serve daily tracking at a published price. What to verify: Which engines are paid add-ons and whether exports carry full answers and cited URLs. Public source: OtterlyAI pricing.

Peec AI

Peec AI’s pricing page lists plans from 50 to 350 prompts with daily tracking on three chosen models and multi-country tracking on higher tiers. Choosing the models lets a team match the tracked engines to the ones its buyers actually use.

Best for: Teams tracking a mid-sized prompt set across several countries. What to verify: Which models can fill the three slots and which tier adds multi-country tracking. Public source: Peec AI pricing.

Profound

Profound positions itself as an enterprise AI marketing platform tracking ChatGPT, Perplexity, Claude, Gemini, Microsoft Copilot, DeepSeek and Google AI Overviews. That home-page engine list is one of the broadest among the tools reviewed.

Best for: Enterprise teams that need wide engine coverage in one platform. What to verify: Pricing, prompt limits and how many runs sit behind each score. Public source: Profound.

Ahrefs Brand Radar

Ahrefs Brand Radar tracks brand visibility in LLMs on Ahrefs’ own index, with custom prompt tracking as a separate product. Because it draws on a prebuilt index, a team can see brand mentions across many questions before writing a panel of its own.

Best for: SEO teams already on Ahrefs that want a broad index view. What to verify: How the index questions relate to your buyers’ questions. Public source: Ahrefs Brand Radar.

Whichever tool you choose, ask it to show the raw answer, the prompt, the engine, the date and the cited URLs behind any score. A composite number you cannot trace back to an answer is harder to act on than your own spreadsheet.

When to move from a manual panel to ongoing monitoring

Ongoing monitoring is justified when AI-assisted research influences a meaningful buying decision, the brand sells in several markets or languages, inaccurate answers create legal risk or several teams publish facts that must stay consistent. It also gives defensible before-and-after evidence for a sustained site and third-party program.

A small local business may not need a platform yet. A carefully documented monthly panel of ten questions can be enough until the number of questions, engines, competitors or stakeholders makes the spreadsheet unreliable. Base the decision on measurement complexity, and verify any vendor’s claims by asking it to rerun your own panel in front of you before you sign.

Frequently asked questions

How do I check if ChatGPT recommends my brand?

Ask ChatGPT eight to twelve questions your buyers ask before they know your name, in a logged-out session with web search on. Repeat each question three to five times in new chats and record how often your brand is named, where it is positioned and whether your domain is cited. Report the result as a frequency, and run the same panel on Gemini, Perplexity and Google AI Overviews separately.

Why does ChatGPT give a different answer every time I ask?

Generated answers are sampled, and the sources an engine retrieves change as its index refreshes. That is why a single screenshot, positive or negative, is weak evidence, and why a manual check uses repeat runs.

Can I pay to have ChatGPT recommend my brand?

No. There is no product that places a brand inside organic ChatGPT, Perplexity or Google AI Overviews answers, and a vendor that guarantees a recommendation is promising something it does not control. What you can influence is the evidence engines retrieve: clear pages with citable facts, and coverage on the third-party sources they already cite.

Is a free AI visibility checker as good as a manual panel?

A free checker such as HubSpot AI Search Grader or the Semrush AI Search Visibility Checker is faster and useful as a first look. A manual panel is slower but lets you control the questions, the interface and the number of runs, and it keeps the raw answers. Many teams use a free checker to spot a gap and a manual panel to confirm it.

Is Canlah AI a monitoring tool or an agency?

Canlah AI is an agency that runs the monitoring panel and then works on the site and third-party changes it points to. Its pricing page lists the GEO service, done for you, from $1,500 a month per AI platform, and a free AI visibility report within 48 hours; after three months of the GEO service, clients can run it themselves with Canlah All-Stars, from $199 a month. Teams that want to operate the panel themselves can use the manual method in this guide or one of the self-serve tools reviewed above.

Method and sources

This guide was rewritten on September 23, 2026 from the earlier August 30, 2026 version. Tool details were checked on current public pages on September 23, 2026 and were not tested through paid accounts or demonstrations. The Canlah AI figures come from a self-audit of canlah.ai; they are API-layer and rendered-browser samples from one date and should not be read as a stable visibility rate or as proof of causation.

• Canlah AI self-audit of canlah.ai, internal export, September 7, 2026. Branded versus non-branded mention counts, Google AI Overview sampling and most-cited domains.
• Canlah AI pricing. GEO service tiers, DeepAudit prices, the Canlah All-Stars step after three months of the service and the free 48-hour AI visibility report.
• Canlah AI free AI visibility competitor report. Engines covered and three-competitor format.
• HubSpot AI Search Grader. Free one-time check, engines and scoring dimensions.
• Semrush AI Search Visibility Checker. Free checker scope and engines.
• OtterlyAI pricing. Plan prices, prompt counts and engines.
• Peec AI pricing. Prompt counts, model choice and tracking frequency.
• Profound. Engines listed on the home page.
• Ahrefs Brand Radar. LLM brand visibility tracking and custom prompts.
• Google Search Central, AI features and your website. First-party guidance on how AI Overviews and AI Mode relate to existing search fundamentals.

See where your brand stands in AI answers. Run the free AI visibility audit →

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