Why your brand is invisible in ChatGPT (and the diagnostic to fix it)

Ask an assistant for a tool that does your product’s job, without giving it your brand name. Save the answer. Then ask it about your product directly. The difference between those answers is a useful place to start an AI visibility audit.

A brand query checks whether the assistant can describe a company it has been prompted to discuss. A category query tests whether it brings that company up on its own. Search rankings and website analytics answer other questions, so keep those records alongside the audit.

If a relevant answer leaves your product out, read the alternatives it suggests and the sources it links. That gives you something concrete to investigate: an outdated description, a missing comparison, a useful discussion, or a question your product may not be well suited to answer.

The audit below separates discovery, factual accuracy and source coverage. Start with a small set of questions you can inspect carefully, then repeat them over time. A first check is a sample of answers, not a forecast of what every customer will see.

How AI engines actually source content

An assistant can answer from information in its model, retrieve pages through a search tool, or use both. Record whether search was enabled and which product you used. The same provider’s app and API can return different sources.

The crawler-citation pipeline

Search access and model-training permissions are different controls. OpenAI uses OAI-SearchBot for ChatGPT search and GPTBot for model training. Googlebot serves Google Search, while Google-Extended controls certain Gemini training and grounding uses without affecting Google Search inclusion or ranking. Check the provider's current documentation before changing an intentional preference.

Training data and live search are different routes by which information can reach an answer. You usually cannot inspect the training material behind a particular response. With a search-enabled answer, you can at least open the returned links and check what they support.

Work on what you can inspect: whether your pages are accessible, whether they explain the product accurately, and whether relevant public sources describe it correctly. An absent answer alone cannot tell you which stage failed.

What "cited" actually means

Record mentions, source links and recommendations separately. They describe different parts of the answer.

• Mention: the answer names your product, whether or not it includes a link.
• Citation: the answer links to a source. Record whether that source is your site, a page about you, or a page about the wider category.
• Recommendation: the answer suggests your product for the task described. Check whether the reason is accurate.

An assistant may link to an article about your category without naming your product. It may also recommend your product without linking to your site. Record both cases; a source link is not automatically an endorsement.

Why some brands win citations and others do not

A single missing answer cannot establish why another brand was chosen. Inspect the cited pages before deciding what to change. A competitor may fit the question better, have clearer documentation, or appear in a comparison you have not read.

Use these checks to decide where further investigation would be useful:

• Source coverage. Which reviews, documentation pages and discussions appear in the returned links? Do they actually discuss the product being recommended?
• Clear facts. Can a reader find the product’s audience, capabilities, price and limitations on the page? Keep applicable structured data consistent with those facts.
• Useful detail. Prefer a worked example, supported measurement or clear explanation to an unsupported claim of superiority.
• Current information. Check dates and verify claims about price, integrations and availability against the product as it works today.

Treat these as questions to investigate, rather than a formula for earning a citation. The audit is useful when it leads to a specific correction you can make and check later.

The audit framework

Keep the prompts, answers and dates in one sheet. Use a fresh conversation for each question so that an earlier mention of your brand does not influence the next answer.

Surface check: direct prompts

Open ChatGPT. Type these three prompts, swapping in your product name:

• "What is [your product]?"
• "Tell me about [your product]."
• "Is [your product] a good tool for [your category]?"

Repeat in the assistants your customers use. Record the product name, date and search setting alongside each saved answer.

For each answer, check the product’s name, category, audience, price and current capabilities. Open any cited sources. Mark an answer as accurate, inaccurate or insufficiently specific, and write down the evidence for that judgement.

Similar product names can produce confusion. If the answer describes another company, save the full response and its sources. Check your own title, about page and public profiles for an unambiguous description before trying to correct a third-party page.

Authority check: category prompts

The category check asks whether your product appears without a brand prompt. Choose questions from customer conversations, support requests and the alternatives people considered before choosing you.

Pick five questions your customer would actually type:

• "Best tools for [problem you solve]"
• "How do I [outcome your product delivers]"
• "Alternatives to [your largest competitor]"
• "[Category] tools for [your customer’s context, e.g. solo founders, B2B sales, indie hackers]"
• "Recommend a tool for [specific job to be done]"

Run the same questions in each chosen assistant. Record whether you are named, how you are described, which alternatives appear and which pages are cited. Keep an error separate from a successful answer that does not name you.

Calculate a mention rate as answers naming your product divided by usable answers. Calculate a separate rate for answers linking to your site. Always keep the counts beside the percentages: one mention in five answers is too small a sample to call a trend.

There is no universal healthy score for this exercise. Compare the same questions over time and compare products within those answers. Changing the question set can move the score even when nothing about your product has changed.

Voice check: sentiment of mentions

When your product appears, read the explanation as a prospective customer would. Does it make an accurate case for the product, and does it describe the limitations fairly?

Read the descriptions carefully. Check whether they are accurate and whether the claims are current rather than eighteen months out of date. Note the tone, whether it reads as neutral, positive or negative, and whether it places you favourably or unfavourably next to competitors. What you are looking for is the gap between the product you sell today and the one the engines still think you sell.

Where an answer repeats an incorrect fact from a cited page, you have a place to investigate. Correct pages you control and request corrections elsewhere with evidence. Then repeat the check; neither the timing nor the outcome is guaranteed.

When the source of an error is unclear, record that uncertainty. Avoid rewriting your whole site to explain one unusual response. A recurring error across saved answers deserves more attention than a single result.

Running the diagnostic

A manual audit is manageable when you start with a few important questions. Save the exact wording and the full answers, rather than only a score. You will need that record to tell whether a later change is meaningful.

The free AfterLaunch scan provides another starting point: customer questions, answers from the leading AI search engines, competitor mentions and cited sources. Its results reflect the measurement surfaces used by the scan; they will not necessarily reproduce a conversation in a consumer app.

When reviewing a scan or your own notes, check:

• Answers and source links. Read the evidence behind a mention or an omission.
• Product accuracy. Check whether the answer describes the right product and its current capabilities.
• Alternatives. Note which products appear on the same questions and why.
• Suggested work. Check that each recommendation addresses a finding you can verify.

The next task should follow the evidence. Fix a demonstrably incorrect product description. Improve a comparison that leaves out a relevant distinction. Contribute to a discussion only when you have a useful answer to its question.

Write down the change and the date, then keep checking the original questions. If the answers improve, look for the changed source before attributing the result to your edit.

Where to go from here

Start with a brand query and a few category questions. That is enough to create a baseline and identify obvious errors, even if you are not ready to set up recurring measurement.

AfterLaunch brings those findings into ongoing growth work, with evidence and drafts for you to review.

The companion articles cover planning the work and checking the implementation.

For context on search traffic, citations and customer discovery:

For the practical work on access, content and measurement: