Most people who start tracking AEO open their AEO tool first and look at visibility scores. Makes sense. But that skips the two metrics that matter most, and neither of them is in your AEO tool.
They're in your analytics platform. LLM traffic and LLM conversion.
LLM traffic: how many visitors are actually arriving from ChatGPT, Perplexity, Claude, or Google AI Overviews.
LLM conversion: what percentage of those visitors become leads or customers. These are the only AEO numbers with a direct line to revenue. Everything else tells you why those numbers look the way they do.
Start there. Then use your AEO tool to dig into the why.
What are the three levels of AEO data?
AEO data exists at three levels, and each one answers a different question:
- Brand overview — Is my brand visible across the topics I care about? How is it trending? This is the executive summary.
- Topic overview — Which topics am I winning or losing? Topics are clusters of related prompts: pricing, integrations, use cases. This is where you spot patterns — consistently absent on competitor comparisons but strong on feature questions.
- Prompt level — For this exact question, what did the model actually say? The exact response, the exact sentiment, the exact position in the answer.
Most brands only look at brand-level data. The actionable insight is almost always at the prompt level.
What are the AEO metrics worth tracking?
Mention rate
How often your brand appears in AI answers, tracked per platform.
!Mention rate, position and sentiment per platform
The same query in ChatGPT and Claude can return completely different results. A brand with 60% mention rate in Perplexity and 10% in Google AI Overviews has two separate problems. An aggregate number makes both invisible. If your brand isn't appearing, nothing else matters.
Position
Where in the response your brand shows up.
Less critical than in Google, but not irrelevant. AI answers are read top to bottom. First brand mentioned gets the most attention. Third in a list of five gets skimmed. AEO Copilot converts position into a score (position 1 = 100 points, position 2 = 85, and so on) so you can track it numerically over time.
Sentiment
Whether your brand is described positively, neutrally, or negatively.
Getting mentioned negatively is often worse than not getting mentioned at all. "Brand X is an option, though users frequently report issues with onboarding" is an active problem. Neutral isn't safe either — an AI that calls you "one option to consider" while describing your competitor with specifics has a sentiment gap that matters. Most AEO tools don't track this.
Source citations
Which of your URLs the AI is actually pulling from.
This is where you go from knowing you have a problem to knowing where to fix it. If your homepage gets cited but your pricing page never does, the AI isn't treating your pricing content as a reliable source. That's a specific content task, not a vague visibility problem.
Competitor detection
Which competitors appear in the same responses, and which appear instead of you.
A 30% mention rate reads differently if your main competitor has 80%. Or 15%. Competitor detection gives you that context. It also shows exactly which questions you're losing — the prompts where competitors appear and you don't.
AEO Score
A single number per prompt, per topic, and overall.
Fifty prompts across four platforms generates more noise than most people can act on. The AEO Score compresses it: visibility 50%, position 30%, sentiment 20%, graded A through F. It tells you which topics need attention this week and which can wait.
Technical LLM readiness
Whether AI crawlers can actually read your site.
A surprisingly common situation: strong content, poor visibility, real issue is technical. Common blockers:
- AI crawlers blocked in robots.txt
- Missing or broken sitemap
- No schema markup
- No llms.txt file
Fixing those tends to move the needle faster than publishing new content, because you're removing a blocker rather than adding more into a broken funnel.
Trend over time
Whether visibility is improving or declining.
!Visibility over time
A snapshot tells you where you are. A trend tells you if anything you're doing is working. Every prompt run is stored historically so you can see:
- Whether a page you published moved the needle on a specific topic
- Whether a competitor's new content is cutting into your mention rate
- Whether a model update quietly changed how your brand gets described
Without history, you're reacting to numbers with no context.
Why does per-platform tracking matter?
!LLM coverage across platforms
ChatGPT, Claude, Perplexity, and Google AI Overviews work differently. Different training data, different retrieval logic, different weighting for citations.
Perplexity leans heavily on live web search. Claude relies more on training data and doesn't browse by default. A brand can be consistently visible in one and nearly absent in the other, and the fix for each is different. An aggregate visibility score hides which platform actually has the problem.
How do you go from data to action?
!AEO recommendations
The most useful diagnostic flow in AEO is top-down: find which topics are underperforming at the brand level, drill to the specific prompts, then read the actual responses.
"My pricing topic has a C grade" becomes "the prompt 'what does [Brand] cost?' returns a vague answer with no specific plan names" becomes "I need a pricing page that actually answers that question." That's the chain. Topic to prompt to response. That's where the work happens.
Frequently asked questions
What is the most important AEO metric?
LLM traffic and LLM conversion — and neither lives in your AEO tool. They're in your analytics platform. These are the only metrics with a direct line to revenue. Mention rate, sentiment, and position explain why those numbers look the way they do.
How is AEO tracking different from SEO tracking?
In SEO, Google Search Console gives you impression and click data for free. In AEO, there's no native analytics. Everything is inferred from prompt sampling — you run queries across platforms and record what the models say. That's why per-platform mention rate matters: it's the closest proxy to "impressions" that AEO tools can measure.
What is a good mention rate in AEO?
It depends heavily on category and competition. A mention rate above 50% across your core prompts is strong for most brands. Below 20% usually points to a content or technical gap. More useful than the number itself: how does your mention rate compare to the top competitor in the same prompts?
Why does sentiment matter if my brand is being mentioned?
Because a negative mention can actively hurt you. If an AI describes your brand as "an option, though users report friction with onboarding," that response is doing damage every time someone sees it. Neutral isn't safe either — being described vaguely while competitors get specific recommendations is a form of invisible underperformance.
How do source citations help me improve AEO?
Citations tell you which of your pages the AI treats as authoritative. If your blog posts are cited but your pricing page never appears, the AI doesn't have enough reliable information about your pricing to reference it. Citation data gives you a concrete list of pages to improve — rather than guessing where to focus.
How often should I check my AEO metrics?
Weekly tracking is enough for most brands. The signals don't move that fast day to day, and a lot of variation between single runs is just noise. What matters is the trend over 4–8 weeks — that's where real changes in visibility (positive or negative) become clear.
Summary
- LLM traffic and conversion in your analytics tool are the most important AEO metrics — they're the only ones connected directly to revenue
- Track mention rate per platform, not as an aggregate — ChatGPT and Claude behave differently and need different fixes
- Sentiment matters: a negative mention can do more damage than no mention at all
- Citation tracking turns a vague visibility problem into a specific content task
- Technical readiness (robots.txt, sitemap, schema, llms.txt) often explains low visibility faster than content gaps do
- Use the topic → prompt → response chain to find exactly where your brand is losing ground and why
For the full monitoring methodology and how to set up recurring tracking: How to monitor brand visibility in AI tools. For a tool comparison covering which platforms actually track these metrics: AEO Copilot vs Peec.ai vs Profound.
AEO Copilot tracks all eight of these metrics across ChatGPT, Claude, Perplexity, and Google AI Overviews. The free plan gives you one brand and 50 prompts to start.