AEO visibility
Polls AI models in parallel for each AEO query and looks for brand mentions. Four tabs: Score, Results, BT10C, Leaderboard.
Executive summary
Three short paragraphs explaining the feature and value.
AEO visibility polls AI models in parallel for every selected AEO query and looks for brand mentions inside each response. Each mention is scored by rank position, the platform that surfaced it, and how completely the brand was named. The composite score is the AEO pillar of the workspace XEO score.
Four tabs slice the result. Score shows the headline AEO number, change since last scan, AI written insight on why the number moved, and the twelve month projection. Results drills into every individual query and every model response. BT10C tracks top ten consistency. Leaderboard ranks every brand the AI models named.
BT10C deserves a moment. Most visibility tools tell you whether the brand was mentioned at all. BT10C tells you whether the brand was mentioned in the top ten consistently across scans, which is the real threshold for AI search. Brands that flicker in and out of top ten get worse buyer recall.
Key highlights
Five capability points teams should know about quickly.
- Polls multiple AI models in parallel
- Brand mentions scored by rank, platform, completeness
- Score, Results, BT10C, Leaderboard tabs
- Twelve month projection in the Score tab
- Leaderboard ranks every named brand competitor
Top FAQs
Five common questions answered for fast practical clarity.
What is the AEO visibility score?
A composite number between zero and one hundred reflecting how reliably the brand appears in AI model answers for the selected AEO queries. It folds rank position, platform breadth, and naming completeness into one figure. Higher means the brand surfaces more, in better positions, across more AI models for buyer relevant questions.
How often should I run AEO scans?
Weekly is the typical rhythm. AI models evolve fast and brand visibility can shift week to week as training data updates, prompt routing changes, and competitor content lands. Monthly scans miss the early signal; daily scans add cost without proportional signal. Weekly hits the standard cadence most marketing teams converge on.
Why does platform matter in scoring?
Different AI models reach different buyer segments and use cases. A brand cited inside one model only is exposed when that model loses share. The platform factor in the score rewards cross platform consistency over single platform concentration. A brand named by every model individually scores higher than one named only by the dominant one.
What does the LLM insight on the Score tab say?
A short AI written explanation of why the score moved in this scan. It reads the actual query and response data, identifies which queries gained or lost ground, flags whether competitor moves drove the delta, and proposes the next remediation action. Insight is probabilistic; numbers are exact; together they explain not just what but why.
Can I export AEO visibility data?
The headline score and per query breakdowns roll into the composite Visibility report PDF, which is the export surface for AEO data. Raw per query and per model scan rows stay inside the workspace as the source of truth; the Visibility report serves as the shareable artefact carrying the underlying numbers, timestamps, and query set version for reproducibility across stakeholders.