AI Answer Engine Optimization
Your buyers ask AI which vendor to pick.
Now you can measure the answer.
ChatGPT, Perplexity, Claude, and Gemini already have an opinion about your clients. AAEO tracks their visibility, position, and sentiment across every AI answer engine — and shows whether your expert marketing moves the needle.
What AAEO tracks
The AI answer layer, measured.
Track every engine
Run buyer-intent queries across Claude, ChatGPT, Perplexity, and Gemini simultaneously. Every answer stored.
Score what matters
Mentioned? What position? Positive or negative? Which competitors edged you out? Every score is auditable back to the raw answer it came from — nothing is a black box.
Prove expert-marketing ROI
Correlate briefings, expert reports, and industry-expert coverage with measurable shifts in how AI recommends your client.
Market attention estimates
How settled is your market in the engines' eyes? Attention concentration, cross-engine consensus, and expert anchoring — grounded in academic work on measuring collective attention in sociotechnical systems, and always labeled as estimates.
Intelligence Briefs
One-click PDF reports your clients actually read — visibility score, platform breakdown, and specific recommendations for your next expert-marketing move.
How a scan is built
The six questions buyers actually ask AI.
Every scan runs a bank of real buyer-intent queries, organized by the moment they represent in a buying decision. Six categories, each measuring something different:
Category Leaders
“Who should be on my shortlist?”
Open questions like “what are the best X platforms?” — the discovery layer. Measures whether you exist in the answer at all, before any buyer knows your name.
Head-to-Head
“How do you compare to the one I know?”
Direct comparisons against named competitors. Measures how the engines frame you when the buyer already has both names — and who wins the matchup.
Use-Case Fit
“Will it work for my situation?”
Segment and scenario questions — “best X for healthcare,” “for mid-market,” “for non-technical teams.” Measures whether engines connect you to the specific jobs you actually serve.
Buyer Objection
“Talk me out of it.”
The concerns stage — “what are X’s weaknesses? Is X hard to implement?” Measures which criticisms the engines repeat. When an answer is wrong or stale, that’s not bad news — that’s the work order.
Pricing & Value
“Is it worth the money?”
Value framing and “cheaper alternatives to X” questions. Measures how engines describe your pricing story — and which lower-cost rivals they volunteer.
Other
Market-specific questions
Anything unique to your market that doesn’t fit the five patterns above — regulatory questions, ecosystem questions, whatever your buyers actually ask.
Each query also carries a purchase stage — Awareness, Evaluation, or Decision — marking where the buyer is in the journey, and a priority reflecting how much that answer matters to pipeline. Which questions belong in yourmarket's bank — and in what mix — is where twenty years of experience comes in.
Designed for companies tracked by
The maturity trap
Too established to worry about search? Think again.
Mature products stopped investing in SEO for a rational reason: they'd already won it. But AI answers are a new competition — and your incumbency doesn't transfer. The engines write tomorrow's shortlists from scratch, and they are perfectly willing to leave a market leader off the list.
of the sources AI engines cite rank in Google's top 10 for the same query. Winning classic search does not carry over — AI citation is a separate contest.
visibility for top-ranked sources when lower-ranked challengers optimize for generative engines, in the founding academic study — the answer layer favors the hungry.
of Google searches now end without a click. The answer itself is the brand touchpoint — including for buyers who already know your name and ask AI to talk them out of it.
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Ready to measure your AI visibility?
Stop guessing whether your expert marketing is reaching buyers through the AI answer layer. Start measuring it.