If you've started paying attention to Answer Engine Optimization, the next question is almost always the same: where do I start with my existing site? The answer is an audit — a structured review of what you have, what AI answer engines can see, and where the gaps are.
This post walks through how to run that audit. It's practical rather than theoretical: specific checks you can run today, what good and bad look like, and how to prioritize what to fix first.
What You're Auditing For
An AEO audit is not the same as a traditional SEO audit. Both care about content quality and technical foundations, but the targets differ. An SEO audit is asking: can search engines find this page and rank it? An AEO audit is asking: if an AI answer engine reads this page, will it understand it well enough to use it as a source?
The three areas an AEO audit covers are:
- Content structure — whether your content is organized so that AI systems can extract clear answers
- Structured data — whether you have schema markup that tells AI systems what your content means
- Content coverage — whether you are actually answering the questions your potential customers are asking AI assistants
These are distinct from keyword density, backlink profiles, or click-through rate optimization — the traditional SEO metrics. You need a different lens.
Step 1: Establish Your Baseline
Before you fix anything, find out what AI answer engines are currently citing you for. This is the baseline everything else measures against.
The process is manual but straightforward. Pick 10 to 20 questions that your customers might ask an AI assistant — the questions you'd expect your best blog posts or service pages to answer. Then ask those questions directly in ChatGPT (with web browsing enabled), Perplexity, and Google AI Overviews. Note which questions your site appears in, which competitors appear instead, and which questions return no relevant sources at all.
This gives you two things: a current visibility score you can track over time, and a list of specific questions where you have the biggest opportunity to improve.
If you want to do this systematically rather than manually, our AEO Tool runs these queries on a scheduled basis and tracks your citation rate across platforms over time — so you get a trend rather than a point-in-time snapshot.
Step 2: Audit Your Content Structure
The single biggest factor in whether an AI answer engine cites your content is whether it can quickly find the answer to the question it is trying to answer.
AI answer engines do not read pages the way a human does. They parse content rapidly, looking for the direct answer to a specific question. If your content structure makes that hard — burying the key point in the third paragraph, or presenting information as flowing prose with no clear organization — you will be underrepresented even if you have excellent information.
For each page you are auditing, check the following.
Does the page answer a clear question?
The best AEO-performing content is organized around a specific question (or a defined set of questions) that a user might ask an AI assistant. If a page is trying to cover too much ground, or does not have a clear question it is answering, it is a weak candidate for AI citation regardless of how much useful information it contains.
Does the answer come first?
Within each section, the direct answer should appear in the first sentence or two. This is the answer-first structure that AI systems favour: lead with the key point, then provide context and elaboration. If your content typically buries the key point after two paragraphs of scene-setting, that pattern needs to change.
Are headings phrased as questions?
Natural language processing systems match user queries to content phrased similarly. If your section headings are vague — "Overview", "Our approach", "More information" — they are difficult to match against specific user questions. Rewriting these as question-style headings that mirror how your audience would phrase the query directly improves match quality.
Step 3: Check Your Structured Data
Schema markup is the fastest technical improvement most sites can make for AI search visibility.
Schema markup is metadata embedded in your page's HTML that tells search and AI systems what your content represents — not just the raw text, but its meaning and structure. AI answer engines use this to understand your content without having to infer it from prose alone.
To check what structured data you currently have, paste your URL into Google's Rich Results Test or Schema.org's validator. What you're looking for:
- FAQPage schema on any page with question-and-answer content
- Article schema on blog posts and editorial content
- Organization or LocalBusiness schema on your homepage
- HowTo schema on any instructional or step-by-step content
Most sites have none of this, or have it only on the homepage. Adding it to your top content pages is a one-time task with lasting value. It is the kind of change that AI systems can interpret in seconds and that directly improves comprehension of what your page is about.
Step 4: Assess Your Technical Foundations
AI systems need to be able to read your pages. This sounds obvious, but a significant share of business websites have technical issues that make their content harder for automated systems to parse.
The key technical checks for AEO:
Page speed: Slow pages get crawled less frequently and less deeply. Use Google PageSpeed Insights to identify significant performance issues. You do not need a perfect score, but serious loading delays are a problem.
Clean HTML structure: Content should live in standard HTML elements — <p> tags for paragraphs, <h2> and <h3> tags for headings — not embedded inside complex JavaScript that renders content only after page load. Some AI crawlers do not execute JavaScript, meaning content rendered client-side may be invisible to them entirely.
Correct heading hierarchy: A single <h1>, followed by logical <h2> and <h3> sections. Skipping heading levels or using heading tags for visual styling only confuses both AI systems and accessibility tools. It is worth fixing even if you have other things to do first.
Step 5: Identify Your Content Gaps
The most valuable output of an AEO audit is often a list of questions you are not answering at all.
Go back to the baseline queries you ran in Step 1. For the questions where your site did not appear, look at what did appear. What content structure do those pages use? What questions do they answer that you do not?
This gives you a content roadmap. The questions where:
- your customers are clearly asking AI assistants
- your competitors or authoritative sources are being cited
- you have the expertise to provide a better or more specific answer
...are the content pieces worth prioritizing. Writing a clear, answer-first piece targeting one of these questions will often outperform trying to retrofit a broad existing page. Specificity wins in AI search — a focused post that directly answers one question usually outperforms a generic overview that touches on many.
Prioritizing What to Fix
Not everything you find needs to be addressed immediately. Here is a practical ordering by return on effort:
- Schema markup on existing top pages — highest ROI per hour, no new content required
- Content restructure on pages with clear question-answering potential — reshaping existing content to answer-first format is usually faster than writing new content
- Heading rewrites — changing vague headings to question-style headings on priority pages is a quick win
- New content targeting identified question gaps — takes longer but compounds over time as each piece can independently earn citations
- Technical fixes — page speed and HTML structure improvements, worth addressing if significant issues exist but rarely the highest-leverage starting point
Start at the top of the list. Most businesses I work with can make meaningful progress on steps one through three in a focused afternoon — before writing a single new word.
Tracking Progress
AEO improvement is measurable, but it plays out over weeks, not days. After making changes, re-run your baseline queries monthly. You're looking for:
- New appearances in AI citations where you were absent before
- Perplexity referral traffic trending upward in your analytics (Perplexity sends referral traffic that shows up in standard analytics tools)
- Brand mentions in AI-generated responses, even when there is no direct link
The risk with manual tracking is that it feels like a lot of effort for uncertain signal — which is why teams either do it inconsistently or stop altogether. If you want visibility data on a reliable cadence rather than sporadic manual checks, the AEO Tool handles the query testing and tracks citation trends across platforms automatically.
Running the Audit
An AEO audit does not require specialist tools to get started. A spreadsheet, a list of the questions your customers ask, and thirty minutes across the platforms where they're asking them will tell you most of what you need to know about your current baseline.
The harder part is knowing what you are looking at once you have the data — whether a gap in AI visibility is a content structure problem, a schema problem, or a content gap problem makes a significant difference to what you do next.
If you would rather have a structured review done for you, or want to understand how your current content compares to what is being cited in your market, that is work I help with through Clear Frame AI's advisory services. Get in touch if you want a direct assessment of where your site stands and what is worth addressing first.