You can't improve what you can't see, and most store owners genuinely don't know whether ChatGPT, Perplexity, or Gemini ever mention their brand. An AI visibility audit answers that question with evidence instead of vibes — and a good one also tells you exactly what's blocking you. Here's what the free Rynex audit checks, how to read each part of the report, and what to do with it.
What is an AI visibility audit?
An AI visibility audit is an automated assessment of two things: whether AI engines can recommend your store (technical readiness), and whether they do (actual mentions in AI answers). Both halves matter, because they fail independently — a technically perfect site can still be absent from every answer, and a frequently mentioned brand can still be leaking accuracy because its product data is a mess.
This makes an audit the natural first step of any Generative Engine Optimization effort. Before you rewrite a single product description, you want a baseline: where you stand, where competitors stand, and which fixes will actually move the needle.
What does the Rynex free audit check?
The free GEO audit takes your store URL and returns a report in under two minutes, covering five areas: site health, AI crawl readiness, real AI mention evidence, competitor gaps, and priority fixes.
Site health. Basic checks that your store is reachable and parseable — the foundation everything else sits on. Problems here usually mean AI systems see broken or empty pages regardless of your content quality.
AI crawl readiness. Whether AI crawlers can actually read your store: robots.txt rules affecting AI user agents, presence of an llms.txt file, and whether your product pages carry valid JSON-LD structured data. These are the mechanical gates between your catalog and any AI engine's retrieval.
AI mention evidence. The part you can't easily check yourself at scale: the audit runs a fixed 9-run simulation panel — three model families (ChatGPT, Perplexity, Gemini) times three category-relevant queries — and records whether your brand or products actually appear in the answers. This is direct evidence, not inference.
Competitor gaps. The same panel shows who is being recommended for your queries when you aren't. Seeing a named competitor take the slot you're missing is usually the moment AI visibility stops feeling abstract.
Priority fixes. A ranked list of what to address first, based on which failures are gating which outcomes.
All of it rolls up into a health score — a single number summarizing readiness and presence together.
How do you read each part of the report?
Read the report top-down as a dependency chain: crawlability findings explain mention findings, and mention findings explain the score. A few interpretation rules keep you from drawing the wrong conclusions:
- A low score with crawl blockers is good news, oddly. It means your invisibility has a mechanical cause you can fix this week, not a reputation problem that takes months.
- Zero mentions across all 9 runs is a clear signal. With three engines and three queries, a clean zero means AI engines currently have no confident story about your brand — expect the fixes to start from crawlability and structured data.
- Partial mentions are the interesting case. Showing up in some runs but not others typically means the models are aware of you but not confident. That's where content clarity and off-site mentions tend to pay off fastest.
- Competitor gaps are your query roadmap. Each query where a competitor appears and you don't is a concrete target: study what sources and structured data support their presence.
- The score is for triage and trend, not bragging. Its job is to tell you where to start and, on re-runs, whether you're moving.
What should you do after the audit?
Work the findings in strict order: crawlability blockers first, then structured data, then content and mentions. The order matters because each layer gates the next — polishing product copy that no AI crawler can fetch accomplishes nothing.
- Clear crawlability blockers. Unblock AI user agents in robots.txt, check that your CDN or bot protection isn't silently rejecting them, and add an llms.txt file. These are hours of work, not weeks.
- Fix structured data. Get valid Product JSON-LD — name, price, availability, ratings — on every product page, consistent with what the page visibly shows.
- Then invest in content and off-site presence. Rewrite key product descriptions so they answer "what, for whom, why" directly, build comparison content for your category's real questions, and earn honest mentions on the review sites and communities AI engines read. Our ChatGPT recommendation guide covers this stage step by step.
If you want the measurement loop to run continuously rather than manually, that's what the Rynex GEO Layer add-on does — ongoing panel tracking, competitor monitoring, AI-optimized product content, and crawlability checks — but the free audit alone is enough to know exactly where to start.
How often should you re-run the audit?
Re-run immediately after shipping fixes, then settle into a roughly monthly cadence. The immediate re-run confirms your changes registered — that the robots.txt edit actually took effect, that the JSON-LD validates. The monthly cadence catches the things you don't control: model updates that reshuffle answers, competitors improving their own presence, and regressions from routine site changes (a theme update that breaks structured data is a classic).
Treat each audit as a snapshot in a series. The single most useful artifact after a few months isn't any one score — it's the trend line, and what it tells you about which of your changes actually moved AI engines to recommend you.
FAQ
What is an AI visibility audit?
It's an automated check of whether AI engines like ChatGPT, Perplexity, and Gemini can find, understand, and actually recommend your store. It combines technical crawlability checks with real evidence of whether your brand appears in AI answers.
Is the Rynex AI visibility audit really free?
Yes. You enter your store URL at rynex.io/geo-audit and get the report in under two minutes, with no charge. Ongoing monitoring and content generation are part of the paid GEO add-ons, but the audit itself is free.
What does the AI visibility health score mean?
It summarizes your store's overall AI readiness and presence: whether AI crawlers can access your site, whether your product data is machine-readable, and whether the 9-run panel actually found your brand in AI answers. It's a triage tool, not a vanity metric.
What should I fix first after an audit?
Crawlability blockers first — a blocked AI crawler makes everything else irrelevant. Then structured data (Product JSON-LD), then content and off-site mentions. Fix in that order because each layer depends on the one before it.
How often should I re-run an AI visibility audit?
Re-run after you ship fixes to confirm they registered, then on a roughly monthly cadence. AI answers shift with model updates and competitor moves, so a single audit is a snapshot, not a permanent grade.