A useful AI visibility report answers three questions: when someone asks an AI assistant about what you do, are you named; if not, why not; and what should you fix first. Anything that doesn't serve one of those — a single composite score with no explanation, a chart of mentions with no context — is decoration. Here's what a report worth reading contains.
What is an AI visibility report?
It's a record of how AI systems — ChatGPT, Perplexity, Gemini, Google's AI Overviews — treat your business when asked questions in your market. You'll see it called an AIO report, a GEO report, or an AI search report. The label matters less than whether it answers the three questions above.
It should show the answers, not just a score
A number alone is hard to act on. The most useful thing a report can include is the answer itself: the words the assistant actually wrote, with your business — and your competitors — highlighted. That's where you learn whether you were recommended or merely listed, and who was named ahead of you.
A composite score is fine as a summary. It shouldn't be the whole story.
It should show who was named instead
Your own absence is only half the story. When an assistant doesn't name you, it names someone — and knowing who is often the most useful line in the report. If the same two competitors appear across most of your questions, their sites and listings are a map of what the assistants find convincing. Study what those pages say and how their details are presented, and you'll usually find the gap in your own footprint quickly.
It should distinguish the ways you can appear
"Mentioned: yes or no" throws away what matters most. There's a real difference between:
- being named in the answer,
- being cited as a source without being named,
- being read by the assistant but passed over, and
- being absent altogether.
Each points to a different fix. A report that collapses them into one number can't tell you which you need.
It should be honest about variation
Assistants don't give the same answer twice. A report built on one check per question is reporting an anecdote. A trustworthy one is built on repeated checks and says so — and it avoids declaring a trend from two data points that differ by chance. If a report never mentions how many times each question was asked, be cautious about its conclusions.
It should end in fixes
The point of measuring is to know what to do next. A report worth reading connects what it found to specific actions: unblock this crawler, add this schema, answer this question on this page. Ideally, each fix is ranked by how much it's likely to matter, so you know where to start.
That's how the Speak Local scan is built: it asks ChatGPT, Perplexity and Gemini your market's questions on a schedule, keeps every answer word for word, records each one on the named / cited / read / absent ladder, and pairs it with a fix list where each task shows the points it gives back.
Red flags in an AI visibility report
- No answer text anywhere. If you can't read what the assistant actually said, you can't check the report's conclusions.
- One check per question. A report built on single checks is reporting noise. Look for how many times each question was asked.
- A trend from two points. Two checks that differ don't make a trend; they're usually variation.
- A single score with no breakdown. A number without the named, cited, read and absent split behind it can't tell you what to fix.
- Vague recommendations. "Improve your content" isn't a fix. "Answer this question in the first line of this page" is.
Questions to ask whoever produces your report
Whether it comes from a tool or an agency, a few questions separate a report that informs decisions from one that fills a slide:
- Which assistants were asked, and were they asked directly?
- How many times was each question checked, over what period?
- Can I see the full answer behind any number?
- How do you tell being named apart from being cited?
- Which fix do you recommend first, and why that one?
A report that can answer all five is one you can act on.