AI Visibility Audit
An AI visibility audit measures how often AI engines name and cite your brand, then identifies what to fix. Learn what a real audit checks and what to ignore.
An AI visibility audit measures how often AI engines name, describe, and cite your brand when answering the questions your buyers ask, then identifies the specific technical and content gaps behind the result.
TL;DR
An AI visibility audit measures how often AI engines name and cite your brand, then identifies what to fix. A full audit covers three layers: what engines currently say about you, which sources they draw on, and which fixes would change the answer.
A full audit covers three layers: what the engines currently say about you, which sources they draw on, and which fixes on your site and off it would change the answer.
Why an AI visibility audit matters
You cannot manage what you have never measured, and asking ChatGPT about your own brand once tells you almost nothing, because answers vary between runs and between engines.
- Baseline: Without a starting measurement, every later change is unattributable and every claim of improvement is a guess.
- Fact correction: Audits surface wrong pricing, outdated positioning, and misattributed features before more buyers read them.
- Source discovery: The audit reveals which domains feed answers in your category, which is usually where the work belongs.
- Prioritization: Dozens of possible fixes exist. An audit ranks them by how much each one plausibly moves citations.
What an AI visibility audit checks
Prompt coverage
A market-sized prompt set, expanded until new competitors stop appearing, run across every engine your buyers use.
Mention and citation rates
How often each engine names you, and how often it credits your pages as sources, reported per engine.
Competitive benchmark
The same rates for named competitors on the identical prompt set, which is the only meaningful comparison.
Source mapping
Every domain cited across the answers, ranked by frequency, including the ones that never mention you.
Fact accuracy
Whether the engines state your pricing, founding details, features, and positioning correctly.
Technical readiness
Crawler access in robots.txt, structured data, llms.txt coverage, rendering, and whether key pages are reachable by AI bots at all.
AI visibility audit vs. AI visibility checker
AI visibility audit: A structured assessment across many prompts and engines, repeated on a schedule, producing a ranked list of fixes with the reasoning attached.
AI visibility checker: A single-run tool that returns a score for one brand or URL. Useful as a first look, too thin to plan work from, because one run of a non-deterministic system is a sample of one.
Most free checkers give you a number and stop there. Findrix runs your market's prompts across seven engines, shows the confidence range under every metric, ranks the sources feeding answers in your category, and writes each fix out in full with copy-paste instructions. Nothing goes live on your site without you applying it. The audit is free, takes about a minute, and requires no signup.
Metrics an audit should report
- Mention rate per engine: The share of prompts where you are named, split by engine because coverage differs sharply between them.
- Citation rate: How often your own pages appear as cited sources rather than being described secondhand.
- Share of voice: Your mentions as a percentage of all brand mentions across the prompt set.
- Sentiment: Whether the descriptions attached to your name are favorable, neutral, or negative.
- Confidence range: The uncertainty band under each figure. A rate quoted without one cannot be trusted to show movement.
How to judge an audit's quality
Three questions separate a real audit from a lead-generation form with a score attached.
First, how many prompts did it run, and were they built for your market or picked from a template? A handful of prompts produces a number with no statistical meaning.
Second, does it show uncertainty? Because engines are non-deterministic, any provider quoting a precise figure with no range is hiding the variance rather than measuring it.
Third, does every finding come with a fix specific enough to hand to whoever runs your site? An audit that ends at diagnosis has left you exactly where you started, holding a number and no plan.
Frequently asked questions
How often should I run an AI visibility audit?
Run a full audit once to establish a baseline and set priorities, then re-measure weekly against the same prompt set. Weekly cadence catches real movement while filtering the run-to-run variance that makes daily checks unreadable.
Are free AI visibility checkers accurate?
They are accurate about what they measure, which is usually one run of a small prompt set on one or two engines. That is a useful first look and a poor basis for a quarter of work. Check the prompt count, the engines covered, and whether any uncertainty is reported.
What should an audit find first?
Usually two things: factual errors engines repeat about your brand, and pages AI crawlers cannot reach. Both are cheap to fix and both cap everything else you might do, since an engine cannot cite a page it cannot read or trust.