OC Systems Agency
AI Search Visibility

When Customers Ask AI Who to Buy From, Are You in the Answer?

Visibility across ChatGPT, Google AI Overviews, Gemini, Perplexity — and Google itself

AI Search Visibility — also called Generative Engine Optimization, or GEO — is the practice of measuring how often AI systems name your business when customers ask who to buy from, then improving the entity, content and third-party signals that decide it. Your customers are asking AI the same questions they used to type into Google, and getting back three or four named businesses instead of ten blue links. Either your name is in that answer or a competitor's is.

Prompt-set benchmarkingShare of visibilityCompetitor mentionsCitation sourcesEntity & schemaMonthly tracking
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Search stopped being a list of links

The questions have not changed. Where they get asked has. A buyer who used to search “best roofing company near me” now asks an assistant, reads a three-name answer, and calls one of the three. The businesses in that answer were chosen from sources — and most business owners have never seen which sources, or who is being named instead of them.

  • ✗Best roofing company near me — asked in ChatGPT, answered with three named companies
  • ✗Best Amazon agency for consumer brands — answered from directories, forums and review sites, not from agency homepages
  • ✗Best corporate gifting company in Orange County — answered from whichever local sources are consistent and current
  • ✗Best HVAC contractor in Irvine — answered before the customer ever reaches a search results page
  • ✗Best Shopify agency for growing brands — answered without a single click to any of the named sites

The cost is invisible, which is what makes it dangerous: there is no line in your analytics for a customer who asked an AI, got three names that were not yours, and called one of them. You do not lose the click. You never get the chance at it.

What the AI Visibility Audit Shows You

Your brand mentions — how often you are named across a defined set of commercially relevant prompts
Competitor mentions — who is being recommended in your place, and how consistently
Share of visibility — your mentions as a proportion of the businesses named on those prompts
Source and citation patterns — the directories, reviews, articles and pages those answers are actually built from
Missing topics — questions your customers ask that nothing on your site answers
Missing service and location pages — the pages an AI would need in order to describe what you do and where
Geographic authority gaps — why you are named in one city and not the next one over
Reputation gaps — where your review profile and third-party presence are working against you
Entity consistency — whether your name, address, category and description agree across the web

Where AI answers actually come from

Nobody edits these answers directly. They are assembled from sources, which is the part that can be worked on.

Where AI answers actually come from1Customer asks an assistant a buying question2The assistant searches and reads sources — your site,directories, reviews, articles, forums3It looks for a business it can describe confidently: clearservices, clear location, consistent details4It names two to four businesses and cites what it used5The customer contacts one of them

What Optimization Work Involves

1

Make the entity legible

Structured data, an organisation entity that agrees with itself everywhere, consistent citations, and a Google Business Profile that is complete and current. AI systems will not confidently recommend a business they cannot pin down.

2

Answer the questions being asked

Service pages, location pages and FAQs built around the actual prompts from the audit — written to be extractable, not buried in prose. This is ordinary good SEO and GEO doing double duty.

3

Build the third-party signals

AI cites sources beyond your own domain. Review strategy, directory and citation consistency, and the third-party presence that makes an answer sourceable rather than self-reported.

Audit, Optimize, Then Track

The audit stands on its own — you can take the findings and act on them yourself. Most people do not want to, which is the rest of the ladder.

Step 1

AI Visibility Audit

A fixed set of the buying questions your customers actually ask, run across ChatGPT, Google AI Overviews, Gemini and Perplexity. You get who was mentioned, who was cited, and what those answers were built from.

$1,200 one-time

Step 2

AI Visibility Optimization

Entity and schema work, the service and location pages that are missing, FAQ and answer structure, citation consistency, Google Business Profile, and the third-party signals AI engines read.

From $2,500

Ongoing

Monthly AI Visibility Tracking

The same prompt set re-run every month: what moved, which competitors gained, what opened up, and what we recommend doing next.

$1,200 / month

Further reading

All SEO & AI Search articles →

Frequently Asked Questions

Can you guarantee ChatGPT will recommend my business?
No, and neither can anyone else. Nobody controls what a model says, the answers vary between users and change between model versions, and any agency promising you a position in ChatGPT, Gemini or Google AI Overviews is selling something that does not exist. There is no placement to buy, no ranking dashboard, and no appeal when an answer changes overnight because a model was updated. What we can do is measure and improve the inputs. We run a fixed set of your buyers' real questions across the major platforms on a schedule, record which businesses were named and which sources each answer was built from, then work on the things that decide whether you are eligible to be named at all: an entity a model can pin down, pages that answer the question directly, and third-party sources worth citing. Judge us on movement across that prompt set over months, reported honestly in the months it goes backwards too.
How is this different from SEO?
It overlaps more than people expect. Both need a crawlable site, real authority and content that answers the question, and most AI answers are assembled by retrieving live pages, so a page that ranks well is a page an AI is more likely to read. AI visibility adds three things on top. First, a legible entity: one name, address, category and description that agree everywhere, so a model can say confidently who you are instead of hedging. Second, extractable structure, meaning a direct answer near the top of a section rather than a conclusion buried in the eighth paragraph, because what gets lifted is a passage and not a page. Third, third-party sources, since these answers are frequently built from directories, review sites and forums rather than from your own marketing. If your site is not indexed or you have no reviews anywhere, start there instead. That is ordinary SEO and it has to come first.
How do you measure something with no Search Console?
By testing directly and repeatably, because there is no console to log into. We agree a fixed set of commercially relevant prompts, the questions your buyers actually ask before they choose, and run them across the major platforms on a set schedule, recording who was named, in what order, and what was cited. Because the prompt set does not change, the month-to-month comparison is meaningful even though any individual answer varies. Be clear about what this is and is not: it is a repeated sample, not a census. We cannot see how many real people asked, we cannot see answers personalised to somebody's account or location, and a single run is close to worthless on its own. What the sample does show reliably is direction and pattern, whether you appear on more of the set than last month, and which competitor keeps turning up on the prompts where you do not.
Which platforms do you check?
ChatGPT, Google AI Overviews, Gemini and Perplexity, plus the traditional Google results for the same queries. The traditional results belong in the same report rather than in a separate exercise, because they are one of the inputs the AI systems read: a query where you are absent from the organic top ten is usually a query where you are absent from the AI answer too, which makes it a useful diagnostic rather than a side note. Two caveats we would rather state up front. AI Overviews do not appear on every query and their presence changes without notice, so an absent overview is not a result about you. And answers vary by location and by the account asking, so we hold the testing conditions steady and treat any single run as one sample rather than a finding. If a platform matters to your buyers and is not on that list, tell us and we will add it.
How long before anything moves?
Honestly, it varies more than we would like, and the reason is worth understanding. Most of these systems answer by retrieving live pages at the moment of the question, so entity and schema fixes can surface within weeks: they change what a crawler reads immediately, with no waiting for a model to be retrained. Content and authority work is slower, because a new service or location page has to be discovered, crawled, judged useful and then chosen over whatever is being cited today. Third-party signals are slower still, and the least under anyone's direct control. There is also a share of what a model believes about your brand that is baked into its weights and only changes when it is retrained, which nobody outside the lab schedules. So expect the technical work to show first and the rest to arrive unevenly. We would not judge this on one month, and we would not ask you to.
Do you do this on your own site?
Yes, and you can verify all of it without asking us. This site explicitly allows GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and Google-Extended in robots.txt, carries Service, FAQPage, Organization and Breadcrumb schema, and submits new content to IndexNow and Google's Indexing API. Fetch the robots file and read the page source if you want to check any of that. We run a benchmark prompt set against our own site on the same schedule we would run yours, and we will show you a real report from it rather than a sample. The site publishes an llms.txt and a machine-readable pricing file, and on that pair we will be straight with you, because it is the kind of thing agencies oversell. Google lists creating llms.txt among its AI-optimization myths, and John Mueller has said no AI system currently uses it. We ship ours for optionality and because AI coding agents do read it, not for citations. Anyone selling llms.txt as a ranking lever is selling a myth Google named.
Is it too early to spend money on this?
It is early, which is most of the argument for it. Competition for AI mentions is well below competition for search rankings in most categories right now, and because the underlying work is entity, content and authority, none of it is wasted if AI search plateaus tomorrow. You are left with better SEO either way. That said, there are businesses we would tell to wait. If your site is not reliably indexed, if your Google Business Profile is incomplete or unclaimed, or if you have almost no reviews and no presence on the directories your category lives on, buy none of this yet. Those are the inputs an AI answer gets built from, and paying for prompt tracking before they exist is measuring a problem you already know you have. Fix the foundations first, with us or without us, and start the tracking when there is something for it to track.

Last reviewed by the OC Systems Agency team.

No agency, including this one, can guarantee that a business will be mentioned, cited or ranked first by ChatGPT, Google AI Overviews, Gemini, Perplexity or any other AI system. This is measurable visibility optimization, not a guaranteed placement.

See How Often AI Recommends Your Business

Give us the questions your customers ask before they buy. We will run them across ChatGPT, Google AI Overviews, Gemini and Perplexity and show you exactly what comes back — including who is being named instead of you.

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