Report sample · Real probe data

Free AI Visibility Report Sample: How Notion Scores in AI Search

This is a real AI visibility report, generated by our probe engine on July 26, 2026. We asked an answer engine 8 buyer-style questions about note taking apps and recorded exactly what it said. Here is every number, unedited.

This sample was generated by our probe engine querying an LLM with buyer-style prompts. Live multi-engine reports (ChatGPT, Perplexity, Gemini, Grok) are generated on demand.

What an AI visibility report measures

An LLM visibility report answers one question: when a buyer asks an AI engine what to buy in your category, does the answer name you? Not your rank on a results page — there is no page one inside an AI answer. Either the answer recommends you, or it quietly sends the buyer to a competitor. If you want the full concept first, read our primers on AI search visibility and what LLM visibility is.

To measure it, the probe engine asks the questions a real buyer would ask — “best X”, “X for small business”, “affordable X for startups” — and records whether the brand appeared, how often, how early, and which competitors were named alongside it.

Prompt-by-prompt results

The core of any AI visibility report: all 8 prompts from the actual run, with the verdict and the rival brands detected in each answer.

Rival names are brands the engine mentioned in the same answer, extracted from the raw response text. “Mentions” counts how many times the brand name appeared in that answer.

Competitor findings

Across all 8 answers, these rival brands kept showing up next to — or instead of — Notion:

Evernote is the most persistent single challenger — it shows up in 7 of 8 answers, including the one Notion lost. Microsoft (counting OneNote) is present in all 8. In a paid Deep Report, this section expands into per-competitor breakdowns: which prompts each rival wins, and which cited sources put them there.

What does an 88/100 actually mean?

Notion’s score tracks its mention rate: the brand surfaced in 7 of 8 buyer answers, and the probe engine scored that run 88/100. For a category leader, that is the expected picture — dominant, but not absolute.

Two honest caveats, because a single number always hides something — this is where an LLM visibility report earns its keep:

• The miss matters. “Top note taking app for small business” is a high-intent, budget-holding query, and Notion is absent from it. A score of 88 with a hole in exactly your target segment is a different situation from 88 with even coverage — the prompt-level table is where the actionable truth lives.
• This is one engine. Visibility varies sharply between ChatGPT, Perplexity, Gemini and Grok because they retrieve and cite differently. A brand can score 88 on one engine and 40 on another. That is why live reports probe multiple engines instead of trusting one.

That is the real value of an AI visibility report: not the headline score, but knowing which specific buyer questions you lose, and to whom.

Frequently asked questions

How is the AI visibility report score calculated?

The probe engine asks buyer-style prompts in your category, records every answer, and scores how consistently and prominently your brand appears — whether you are mentioned at all, how often, and how early in the answer. In this sample, Notion appeared in 7 of 8 answers and scored 88/100.

Is 88/100 a good score?

It is a strong score — the kind category leaders earn. It means the engine names the brand in nearly every relevant buyer answer. But notice the one miss: “top note taking app for small business.” Even leaders have blind spots, and a high single-engine score can hide weaker visibility on other engines.

How often is a report updated?

Reports are generated on demand from live probes, so every run reflects the engines’ current answers. AI answers shift as engines retrain and new content publishes, so re-check monthly at minimum — visibility is a trend line, not a trophy.

How is this different from an Otterly report?

Otterly is a subscription monitoring platform for ongoing tracking. llmvisibilitycheck.com starts with a free one-time baseline — you see whether AI engines recommend you before paying anything — then offers fixed-price deep reports instead of a recurring subscription. Both measure AI search presence; the difference is pricing model and entry point.