What Does AI Say About Your Business? 8 Questions SiteSignal Helps You Answer

Quick answer: To find out what AI says about your business, ask ChatGPT, Gemini, Perplexity and Google AI Overviews the questions your buyers ask, then check four things separately: whether you are mentioned, recommended or cited; whether the facts are right; who wins instead and why; and whether AI crawlers can reach your site. SiteSignal runs those checks daily and turns them into a weekly list of fixes.

You open ChatGPT, ask for a product like yours, and see three competitors recommended. Your business is missing.

You try another question. This time your company appears, but the description includes a service you stopped offering. A third answer links to your website while recommending someone else.

What should you do with that? Business owners, marketers and agencies ask versions of this question every week on Reddit and in OpenAI's own community forum. This guide takes eight of those questions, explains a practical way to answer each one yourself, and shows which SiteSignal feature helps. The discussions show what people are worried about. They are not SiteSignal testimonials, and nothing here guarantees that a change will earn more recommendations.

Why this matters now

ChatGPT passed 900 million weekly active users in February 2026. When a buyer asks it for a recommendation, the answer usually names only a handful of brands, and there is no page two to scroll to.

Our own data shows how often AI gets the basics wrong: in SiteSignal's checks, 17% of AI fact-checks about brands were flat wrong (out of 4,903 checks). And in our crawler audits, 11 of 26 sites (42%) failed AI crawler access checks, which means some engines could not read them at all.

The 8 questions at a glance

1. How do I know whether AI mentions or recommends my brand?

Short answer: Ask the questions your buyers ask in each AI engine, repeat them over time, and record your role in every answer: mentioned, recommended, ranked, cited or absent. These are different outcomes. An answer can cite your guide while recommending a competitor, and counting both as a win hides the problem.

In an r/DigitalMarketingHack thread, a poster asked whether anyone actually tracks if their brand shows up in AI answers. Most teams have a process for Google rankings and nothing comparable for ChatGPT or Perplexity.

Consider this hypothetical answer: "Company A publishes a helpful guide on this topic, but Company B is the better choice for small teams." Company A earned a citation. Company B earned the recommendation.

How to approach it

1. Collect questions from sales calls, onboarding and support, including the buyer's situation: "What tools suit an agency managing several client websites?" beats "best monitoring tool".

2. Group them by buying stage: Awareness, Consideration and Evaluation.

3. Run each question several times per engine. AI answers vary from run to run, so one result is an anecdote, not a measurement.

4. Keep a stable core set so you can compare month to month.

What SiteSignal shows

• Visibility, mention, recommendation, ranking and citation rates

• An 8-level score for each answer, from "Recommended + Cited" to "Not Visible"

• Visibility over time next to every competitor you add

• AI share of voice by engine, source composition and brand sentiment

• Every cited domain and URL, exportable

See the AI Visibility feature.

2. What happens when AI gets our business facts wrong?

Short answer: An AI hallucination is when an AI engine states something false about a business. Save the exact answer, find the wrong statement and its source, make sure your own site states the correct fact clearly, fix outdated listings, then keep checking. Publishing a correction and seeing a corrected answer are two separate milestones.

In an OpenAI Developer Community thread from June 2026, a user complained that ChatGPT pulled outdated or wrong business listing details for specific locations. OpenAI Support replied that search results can be outdated, suggested checking the cited business source, and asked for a concrete example of an incorrect result.

That's a useful habit: keep the evidence before you act. In our UK workwear research, contact details were the facts AI got wrong most often. Support emails were wrong 30% of the time.

How to approach it

1. Start with facts that change a buying decision: price, services you offer today, locations, refund terms and what each plan includes.

2. For each error, record the question, the answer, the wrong statement, the correct fact and any cited source.

3. Check that your own pages state the fact plainly. If an old directory entry is the source, fix that too.

4. Re-check over time and note when each engine catches up.

What SiteSignal shows

• Daily fact-checks in every engine, marked accurate, partial match, hallucinated or insufficient data

• Custom variables, so you can check any business fact, not only the defaults

• An accuracy timeline per AI provider

• Fix duration: how long each engine takes to catch up once you correct the record

See Brand Accuracy, or read our guide to detecting and fixing AI hallucinations about your brand.

3. Why does AI recommend a competitor instead of us?

Short answer: Read the full answer, not a summary. Note who appeared, the reason the AI gave (budget, setup, a specific feature), and which sources it cited. Then open those sources. Competitors usually win because the pages AI trusts describe them better for that buyer's need, not because of a single ranking factor.

In a 2024 OpenAI community thread, a London business owner said ChatGPT recommended competitors even though, in their view, their business was stronger on search visibility, services and reviews. That's one person's account, not proof of how ranking works, but the question behind it is the right one: what evidence explains the answer?

How to approach it

• Who appeared? List every business, including unfamiliar ones.

• What reason was given? Look for the requirement the answer emphasised.

• What supported it? Open each cited page and check whether it covers that requirement, and whether it describes you accurately.

End with a concrete brief, not a vague goal. "Explain how our reporting works for agencies, include the plan details and show a sample report" is a task. "Improve our AI authority" is not. And don't answer every lost question with another "best tools" article.

What SiteSignal shows

• Full AI responses for competitor questions

• Every cited source, with mention counts

• Top recommendation vs. runner-up for each question

• A prompt library you build by hand or CSV import, tagged by funnel stage and category

See Competitor Analysis.

For the signals behind these choices, see how AI models decide which brands to mention.

4. What should we actually write about?

Short answer: Look at the searches AI runs behind a question. Query fan-out is when an AI engine breaks one question into several searches before it answers. Those sub-questions show what a complete answer needs to cover. Treat them as research input, not a publishing schedule: some belong on an existing page, some in an FAQ, a few deserve a new article.

A broad question hides several smaller decisions. Someone asking for software recommendations may also care about setup time, integrations, price and maintenance. In an r/AISEOTricks thread, a poster asked whether anyone builds content around query fan-out. An r/SEO thread asked whether people actually use fan-outs in practice. Both are fair questions to ask before you turn every sub-query into an assignment.

How to approach it

For a hypothetical question about website monitoring, the fan-out might suggest covering: what problems to monitor, how setup works, who receives alerts, what needs a developer, and what belongs in a client report. That might be one stronger feature page and an FAQ, not five new articles. Write the brief around the reader's decision, then check the finished page as a buyer would: can they find the answer quickly, and are conditions and limits clear?

What SiteSignal shows

• Five rates per question, per engine, with 30-day history

• Intent classification with the reasoning shown

• Query fan-out for ChatGPT, Perplexity and Gemini, tagged by intent and funnel stage

• Who AI picked first, the complete answer and every source behind it

See Prompt Diagnosis & Query Fan-Out.

5. Can AI systems reach the information on our site?

Short answer: Check that your key pages load, respond quickly and allow the right AI crawlers. Be specific about which crawler: OpenAI's GPTBot is used for model training, while OAI-SearchBot powers ChatGPT search, and OpenAI says each setting is independent. A site that is down, slow or blocking search crawlers cannot be cited, however good its content.

A user in the OpenAI Developer Community asked whether they could submit their website to ChatGPT the way you submit a site to Google. You can't, which makes technical access more important. According to OpenAI's crawler documentation, OAI-SearchBot "is used to surface websites in search results in ChatGPT's search features." "Allow AI bots" is too vague for a developer to act on. Name the bot and the purpose.

How to approach it

Turn every health finding into a technical task: the URL, the issue, when it happened, and how to confirm the fix. Keep access and outcomes separate. Fixing an access problem means AI can now reach the page. It doesn't, on its own, mean AI will recommend you.

What SiteSignal shows

• Uptime checks every 5 minutes from outside your site, with a 12-hour timeline

• Response time and performance score

• Daily SSL certificate validation

• AI crawler access checks (GPTBot, PerplexityBot and more)

• Nothing to install and no code to add

See Website Health, or read how AI crawlers access websites.

Comparing uptime and ranking tools? See our website monitoring tools roundup.

6. Which pages should we improve first?

Short answer: Start with the few pages tied to buying decisions: homepage, pricing, your main service or feature page, and a key comparison. Give each a clear purpose and audience, check that important facts are stated explicitly, and keep a change log so you can connect updates to later answers.

In an r/SEO_tools_reviews thread, a builder said they were tired of running the same SEO audit over and over. The underlying complaint is common: audits produce long lists without saying what matters or what to fix first.

How to approach it

Alongside any audit, ask: can a new reader tell who this page is for? Are prices, limits and conditions explicit? Does it answer what your sales team hears every week? If a feature page promises "powerful reporting" but never says what a report contains, the fix is to describe the report, show an example and say who uses it. Log the page, the problem, the change and the date.

What SiteSignal shows

• Add pages one at a time or in bulk

• Page type, goal and audience for every page

• Weekly page health audits, with recommendations so AI engines can understand and cite the page

See Page Audits.

Want a quick check before committing? See our list of free AI search and SEO audit tools.

7. What should our team do with all this information?

Short answer: Turn findings into a short, ranked list of tasks. Each task needs the observation, the change, an owner (developer or content writer), and how you'll verify it. Separate known repairs from hypotheses: fixing a wrong price on your site is verifiable today, while expecting it to change an AI answer is something to monitor.

In an r/seogrowth thread, a builder asked whether AI visibility can be made actionable. A score starts a conversation, but it doesn't assign work. Compare "Improve brand accuracy" with "Review Tuesday's pricing answer, confirm the wrong statement, and update the public pricing explanation." Only the second one gets done.

What SiteSignal shows

• A new ranked plan every week, with the first within 24 hours of signing up

• Every task tagged developer or content

• Each task linked to the buyer question and AI answer behind it

Does acting on it work? The Uniform Consultants, a UK uniform consultancy and SiteSignal client, went from 7.3% to 13.6% of brand mentions in AI answers to its buyers' questions between May and September 2026. That's one client, not a promise, but it shows the kind of change daily tracking lets you see.

See the Weekly Action Plan.

8. How do we explain AI visibility to clients?

Short answer: Report decisions, not vanity metrics. Show the buyer questions you monitor and why they matter, a few real answers as evidence, the work completed, and what is still uncertain. Keep AI answer data separate from visits, leads and sales, which need your analytics.

In an r/agencynewbies thread, a poster asked how agencies report AI visibility without it becoming another vanity metric. A good line for a client report sounds like this: "We reviewed questions about multi-location support, found our public explanation was incomplete, updated the page, and will keep checking how answers describe it." It is specific about the work and doesn't claim a result you haven't seen yet.

What SiteSignal shows

• Reports generated automatically on the 3rd of every month, or for any date range

• White-label reports with your logo and colors (Agency plan)

• Unlimited team seats with Owner and Developer roles

• Alerts for AI visibility, hallucinations, uptime and SSL

• An MCP server, so you can use SiteSignal from Claude, Cursor or your own AI agents. On the Agency plan you can also create branded prospect reports there, from domain to finished report

See Reports & Team, or read how SEO agencies offer AEO services.

How SiteSignal collects the data

• Engines: ChatGPT, Gemini and Perplexity through their official APIs. Google AI Overviews results are retrieved from live Google search results. Claude is coming soon at no extra cost.

• Location: each site's location and audience profile are set to match its target market, so answers stay close to what a real buyer sees.

• Questions: you choose them. SMB plans include 30 unique questions a month, and the Agency plan includes 60 for every client domain.

• History: every answer is kept, so you see trends instead of one-off snapshots.

What SiteSignal doesn't do

• It doesn't make AI recommend you on its own. It shows what to change. Your team or agency still makes the changes.

• It doesn't track every possible question. You pick the ones that matter.

• It isn't an SEO suite. It has no backlink analysis, keyword research or rank tracking. It's built to sit alongside tools like Semrush, Ahrefs and Google Search Console.

How to start without turning this into a big project

1. Pick one product, service or customer segment.

2. Choose a small set of buyer questions from sales calls, support requests and public discussions, including questions about your business facts.

3. Record a baseline. Review mentions, recommendations, citations, accuracy and competitors separately.

4. Check a few key pages for availability and for whether they answer what those buyers need.

5. Make one or two specific changes, assign an owner and log the date.

6. Re-check the same questions and compare against the baseline.

In SiteSignal, setup is your domain plus a few competitors, monitoring starts within minutes, and your first action plan arrives within 24 hours. See how it works.

Pricing

SMB (BYOK) is $89 a month, SMB is $299 a month, and Agency is $399 a month with 3 client domains, plus $89 a month for each extra domain. Every plan includes all four engines, daily hallucination checks and the weekly action plan. Every plan starts with a 7-day free trial, and you don't need a card. See the pricing page.

Give every finding a next step

The people in these discussions want more than "are we in the answer?" They want to know if the description is accurate, what competitors do differently, which pages need work, and how to explain it. Start with evidence you can inspect, make changes your team can explain, and keep a record of what happens next.

Start a 7-day free trial, no card needed, or run the free AI visibility checker first for a quick look. If you have questions or think we're missing something, tell me. I read every reply.