How to Run an AI Visibility Audit for Your Own Website

The stakes are real. When a Google AI Overview appears, users click a traditional result in only 8% of visits, versus 15% when no AI summary shows, according to Pew Research Center’s July 2025 study of 68,879 searches. That is nearly half the clicks gone, and a brand the answer never names does not get them.

And a bad first result is normal. In our 500-query Houston real estate study, an estimated 94.0% of the Houston Association of Realtors’ 50,000-plus members were never named in 2,000 AI answers, so if your audit comes back ugly, you are in a very large majority.

What is an AI visibility audit, and how is it different from an SEO audit?

An AI visibility audit checks whether AI engines name and cite your brand in their answers, while an SEO audit checks whether Google can crawl, index and rank your pages. The win conditions differ, as the table shows.

The two used to move together and now diverge. Search Engine Journal, reporting BrightEdge data, says AI Overview coverage grew about 58% in the twelve months from February 2025 to February 2026, and a rank tracker cannot see any of it. Ahrefs found that only about 12% of AI-cited URLs rank in Google’s top 10 for the same prompt, with Perplexity highest at 28.6%, one of the AI SEO impact ranking statistics US teams should be working from.

Step 1: Build your prompt library

Write 15 to 25 questions your buyers actually ask, in their words, not yours. Group them by intent so you can read the results cleanly later: definitional (“what is X”), comparison (“X vs Y”), and recommendation (“best X for Y”). Weight the set toward recommendation prompts, which is where a buyer meets a brand name inside an AI answer. Fewer than 15 prompts and one odd answer distorts the read, while more than 25 and you spend the afternoon logging. An agent or brokerage should skew toward recommendation and comparison, since that is the moment a buyer or seller decides who to call.

Skip your own brand name in most prompts. You are testing whether AI reaches for you unprompted, the way a real buyer’s session would.

Some examples for a real estate agent who works the suburbs southwest of Houston:

• Definitional: “what does a buyer’s agent do in Texas”
• Recommendation: “best real estate agent in Sugar Land for first-time buyers”
• Comparison: “is Katy or Cypress better for a young family”
• Hiring: “who should I hire to sell my house in Sugar Land”
• Problem-led: “how do I sell my house while buying another one”

Step 2: Audit your brand in ChatGPT, Perplexity, Gemini and AI Overviews

Run each prompt through ChatGPT, Perplexity, Gemini and Google AI Overviews or AI Mode. Do it logged out or in an incognito window, because a logged-in engine leans on your past chats and shows you a flattering answer no stranger would get. Then run each prompt a second time on a different day, because these systems are non-deterministic and one response is a sample, not a verdict, and anything that appears in only one run stays unconfirmed. Our guide to checking whether ChatGPT recommends your brand covers why fresh chats and repeat runs matter, with the SparkToro data on how rarely the same list comes back, and walks a ten-minute single-engine version. For the Perplexity run, how to get cited by Perplexity shows how to read its numbered sources and which two crawlers to allow.

15

sources per response is the average for ChatGPT, against 3 for Gemini, per Semrush’s 2026 AI Visibility Index.

The engines cite from different pools. Per Semrush’s 2026 AI Visibility Index (126 million U.S. prompts, January to April 2026), ChatGPT cites an average of 15 sources per response and Gemini an average of 3. Optimize for one and you can still be invisible on the rest.

Treat AI Overviews and AI Mode as two separate runs, not one. If you would rather automate that half of the work, our review of the best AI Mode SEO tracking tools covers which ones query AI Mode directly and which simply relabel AI Overviews data.

Step 3: Log appearance, position and citations in one sheet

Record one row per prompt-and-engine pair. For each, note whether your brand appeared, roughly where in the answer, whether the engine cited one of your own pages, which competitors got named, how you were framed, and every source URL the answer linked. This sheet is the audit. Everything after it is reading the sheet.

Build these columns and you have a reusable template you can rerun every month:

Reading the citations

Pull every URL from the “Source URLs” column into one list, then sort it into three buckets: your own pages, neutral third parties (Reddit, review sites, editorial roundups), and competitor pages. That split shows where the engines’ trust lives, and most brands find their own domain barely shows while third-party pages do the heavy lifting.

Step 4: Run the llms.txt crawler access check

Before you blame your content, confirm the engines can even reach it, because a blocked crawler makes the best page on the internet invisible. robots.txt shows only what you allow, not what your host delivers: when we tested our own site on 14 September 2026, the host’s CDN returned HTTP 429 to 8 of 8 cache-miss requests carrying the full GPTBot user agent, while seven other user agents, a browser among them, got HTTP 200 on all 56 of their requests (the test). Our guide to checking whether AI crawlers can reach your site gives the four curl commands.

Then run this short list:

• Open robots.txt and confirm it does not block GPTBot, Google-Extended, ClaudeBot or PerplexityBot.
• Load a key page with JavaScript disabled. If the content vanishes, crawlers may see nothing either.
• Check that RealEstateAgent, FAQ and review schema are present and valid on your money pages. If you are not sure what to look for, here is how to audit your schema markup for AI search.
• Confirm your pages return real HTML, not a client-side shell.

Fetch and grade your llms.txt

Go to yourdomain.com/llms.txt and see what loads. This file is a plain-text map of your most important pages, written for AI systems. We grade it on every audit as a standing rule. A good one lists your key pages with short, accurate descriptions. A missing or empty one is a fast, cheap fix. It is not a silver bullet, but leaving it blank is a signal you skipped the basics. Our explainer on what an llms.txt file is and how to build one covers the format.

Step 5: Score it into one citability number

Turn the notes into a single 0 to 100 score you can track month over month, weighting five inputs from your sheet: appearance rate, citation rate, share of voice, accuracy of framing and position in the answer.

Here is a rubric you can use. The weights are our suggestion, not an industry standard, so keep them fixed between runs.

How to measure AI share of voice

Count how many times your brand is named across the whole prompt set and divide that by the total brand mentions, yours plus every competitor. That percentage is your share of voice, and the benchmarks to compare it with are in the FAQ below. Track the number, not the feeling.

To turn that single reading into a scoreboard you can defend month after month, our method for tracking competitor rankings in AI search covers the run counts and clean-room rules that separate a real move from resampling noise.

Step 6: Why a Perplexity citation check will not predict ChatGPT

The same low score means a different fix on each engine, because they source answers so differently that chasing Google rankings moves one and does nothing for another.

The clearest proof is overlap with Google. Per Semrush’s July 2025 study of 5,000 keywords and over 150,000 citations, Perplexity’s cited domains overlap Google’s top 10 by over 91%, Google AI Overviews by about 86% and Google AI Mode by about 54%, with ChatGPT the lowest of the platforms studied. So better rankings can lift Perplexity while barely touching ChatGPT.

Why isn’t my brand showing up in ChatGPT?

Usually because ChatGPT does not lean on Google rankings the way you assume. It rewards structured facts about your brand and mentions on sources it already trusts. If you rank well but ChatGPT ignores you, the lever is off-site authority and clean entity data, not another push for position one. Our diagnosis of why brands go invisible to AI breaks down the common causes, and how to rank in ChatGPT shows what 2,000 measured Houston answers say about how ChatGPT picks firms in a city.

Step 7: Turn findings into a Fix / Build / Influence list

Every finding maps to one of three actions: fix what is broken, build what is missing, influence what lives off your site. Sort the list by how much each fix is likely to move a citation and start at the top.

• Fix: unblock crawlers in robots.txt, add missing RealEstateAgent and FAQ schema, publish or repair your llms.txt. Fast wins that remove hard blocks.
• Build: write answer-shaped capsules on money pages, publish neighborhood and comparison pages, structure your facts so AI can lift them cleanly.
• Influence: earn third-party mentions and reviews. These engines lean on what neutral sources say about you, so review sites, portals, roundups and community threads count.

How often should you re-run the audit?

Monthly, with the same prompt set each time. These metrics move quickly, and a quarterly cadence misses shifts you could have acted on. If you would rather have that re-run happen on a schedule, our independent review of the AEO tools that track brand mentions in ChatGPT covers what the free checkers and the paid trackers each buy you.

The Princeton-led GEO paper (Aggarwal et al., arXiv 2311.09735) found that generative-engine optimization can lift a page’s visibility in AI responses by up to 40%. The audit is how you find which pages have that room to gain.

How does an AI visibility audit work for a real estate agent or brokerage?

The seven steps stay the same, with two changes: write the prompts per neighborhood and per intent, and give portals their own bucket in the citation log. CiteVantage’s 500-query Houston study put 500 real estate queries to four AI surfaces in September 2026, and three of its findings change how you build and read the audit:

Houston study

83.3%

of the real agents named appeared on only one surface, which is why step 2 runs every engine separately.

Photo: Arian Fernandez, Pexels

• Areas and intents are separate contests. An estimated 82.6% of the agents, teams and brokerages AI named appeared in just one of 40 areas, and 94.0% of the firms named in new-build answers were absent from the generic answer for the same area, so “best realtor in Sugar Land” and “new construction in Sugar Land” each need their own prompts.
• Each engine names a different set of agents. 83.3% of the real agents named appeared on only one surface, which is why step 2 runs every engine separately.
• Your own site is a small part of the answer. A firm’s own domain was cited in 8.4% to 10.4% of the answers naming it, while portals and agent referral networks took 43.6% of all citations.

So when you sort citations in step 3, split the third-party bucket into portals (Zillow, Realtor.com and your local MLS portal) and everything else. Google Business Profile belongs in the log too: Local Falcon’s Realtor AI Visibility Index (August 2026), a vendor measurement, reported that it supplied 36.6% of AI citations on near-me realtor queries across the 100 largest US cities, one of the sourced figures on our real estate SEO statistics page.

If you would rather not run the steps by hand, our Free AI Visibility Audit takes your website address and what you sell, runs 50 buyer questions through each of ChatGPT, Perplexity, Gemini and Copilot, and sends back the 200 screenshotted answers with a 0 to 100 score and your three biggest citation gaps within 48 hours. It covers steps one, two, three and five, uses Copilot where this guide uses AI Overviews, and needs no call or card. Or you can hand it to a GEO agency instead and skip the afternoon entirely. To see the finished format first, we published a redacted sample AI visibility audit for real estate with the full question set, the scorecard and a firm that appeared in none of 38 AI answers. Our real estate AI visibility service picks up where the audit leaves off, and the Bright Realty case study shows what that next step produced for one property network.

For the shorter ten-minute version of the first step, see how to check if ChatGPT recommends your brand.