What is an AEO (Answer Engine Optimization) audit?

An AEO audit checks whether AI systems — chat assistants, AI-powered search summaries, and agents that browse the web on a user's behalf — can correctly read, understand, and cite your site. It's a different lens than traditional SEO: a page can rank well and read cleanly for a human while still being effectively invisible to a model, if the content it needs (structured data, brand identity signals, answer text) isn't present in the page's underlying markup.

Why didn't our schema markup show up even though our social links were visible in the footer?

Because visible and machine-readable are not the same thing. Our social links rendered as unlabeled icons 97% of the way down the page — a person scrolling to the bottom sees them instantly, but a crawler reading top-down often stops before it gets there, and an icon with no accessible label or rel="me" attribute carries no identity signal even if it does. Separately, we had zero Organization or WebSite JSON-LD anywhere on the site, which is the structured data that tells a model who you are in the first place.

Does hiding FAQ answers behind a click-to-expand accordion hurt SEO or AEO?

Yes, if the answer text isn't rendered into the page's HTML until a user clicks. Our FAQ accordion used to unmount each answer until it was expanded, which meant our most persuasive, highest-intent content — the exact questions buyers ask — did not exist as far as any crawler or model reading the page was concerned. The fix wasn't changing the copy; it was switching to a CSS-based collapse so the answer text is always present in the DOM, with FAQPage schema describing it.

What is the difference between SEO and AEO?

SEO optimizes for ranking in a list of links a human then clicks through. AEO optimizes for being the source a model reads, understands, and cites directly in a generated answer — often without the user ever visiting your site. The two overlap heavily on fundamentals (crawlability, page speed, content quality) but diverge on specifics: AEO cares far more about structured data, unambiguous entity identity, and whether your actual answer text is present in the markup rather than hidden behind interaction.

How do I know if AI assistants can actually read my site correctly?

Fetch your own pages the way a crawler does — view source or curl the URL rather than the rendered browser page — and check whether your key claims, FAQ answers, and identity signals (Organization schema, social profile links with proper labels) are actually present in that raw HTML. If content only appears after JavaScript runs or a user interacts with the page, a model reading the static markup may never see it. A third-party audit is useful precisely because it checks this from the outside, the way an external system actually would.

We Scored 49/100 on an AEO Audit. Here Is What It Found and What We Fixed

DocumentPro

We'd just spent two weeks polishing our marketing site — restructuring the blog, sharpening the positioning, tightening the copy. By every measure we knew how to check, it was in the best shape it had ever been.

Then we ran it through an AEO (answer-engine-optimization) audit and got a score of 49 out of 100.

Two findings stood out immediately: no schema markup detected, and no social media links found. Our first reaction was that the crawler had to be wrong — we could see our social links in the footer of every single page.

It wasn't wrong. It was seeing our site the way an AI answer engine sees it, and that turned out to be very different from the way we saw it.

What Was Actually Going On

Once we started digging, the two flags opened into something bigger.

We had no brand identity data at all. Structured data — the machine-readable summary that tells AI systems who a company is, what it does, and where else it exists online — was completely absent from every page of our marketing site. Not out of date. Not misconfigured. Simply never built. We'd been optimizing copy for humans while giving AI systems nothing to work with.

Our social links were technically present and practically invisible. They rendered in the footer of every page — but 97% of the way down the document, as bare icons with no text label attached. A person scrolling to the bottom sees them instantly. A crawler reading top-down often stops before it ever gets there, and even if it arrives, an unlabeled icon carries no meaning. The audit reported them missing because, functionally, they were.

Our best content was hidden behind a click. This was the one that stung. Our FAQ section answers the exact questions buyers ask — how fast can you launch, is your data secure, why not just build this yourself. Those answers only loaded into the page after someone clicked to expand them. Which meant that to every crawler and every AI model, our most persuasive, highest-intent content simply did not exist.

And a couple of things we'd never have gone looking for. Our analytics tag was firing twice on every page view. Our deployment process had a known weak spot where some pages could quietly keep serving an older version of themselves. Neither showed up in the audit — both surfaced because the audit sent us looking.

Why This Mattered to Us

DocumentPro sells a document extraction API to software platforms. Increasingly, the engineers and product leads evaluating a vendor like us don't start with a search results page — they start by asking an AI assistant which APIs to consider.

That shift changes what a marketing site has to do. It's no longer enough to be persuasive to a human who has already landed on the page. You have to be legible to the systems deciding whether to mention you at all. A model can only recommend what it can read.

We were failing that test in the least visible way possible: the site looked great, converted fine, and read well. Nothing was broken in any way a normal review would catch. We were simply invisible to a channel we didn't realize we were competing in — and we'd have stayed invisible indefinitely, because everything we knew to look at was green.

What We Changed

Four focused pieces of work:

We gave the brand a machine-readable identity. Every page now carries Organization and WebSite JSON-LD describing who DocumentPro is, what category we operate in, and which official profiles belong to us — including our social accounts, stated as verified brand properties rather than buried at the bottom of the page.

We made our best content readable. FAQ answers now render into the page itself instead of appearing only on click. The visual experience is identical; the difference is that the content now exists for everything else reading the page. We added the same treatment — plus FAQPage, BreadcrumbList, and SoftwareApplication schema — to our pricing, solution, and blog pages.

We fixed the things the audit led us to. The duplicate analytics tag is gone. The deployment weak spot — a stale build-cache bug that could quietly keep an old page live after a release — is closed.

We built a guardrail. The single most valuable outcome. Our deployment pipeline now automatically checks, on every release, that our brand data, social profile signals, and FAQ answer text are present and correctly rendered on every page. The gap the audit found had gone unnoticed for months. It cannot go unnoticed again — if it ever breaks, we know before the next release ships.

Where We Landed

Concretely, on our marketing pages:

| | Before | After | |---|---|---| | Pages with brand identity (Organization/WebSite) schema | 0 | Every page | | FAQ answers present in rendered HTML | None | All of them | | Position of social profile signals | Bottom 3% of the page, unlabeled | Labeled, with rel="me", in the structured data on every page | | Automated checks protecting all of it | None | Every deployment |

Some of what the audit flagged — earned media coverage, for instance — is work no code change can do on its own. That's a real gap, and we're treating it as one, not a checkbox we can tick from the codebase.

But the part we could fix, we found and fixed quickly. We would not have found it without an external audit looking at the site the way a machine actually does.

In Our Words

"We'd just finished what we thought was a thorough cleanup of our marketing site. The audit gave us a 49 out of 100 and flagged two things we were sure were false alarms.

They weren't. Our brand data didn't exist, and our social links were technically on the page but effectively invisible to anything reading it. Worse, chasing those two findings led us to discover that our entire FAQ section — our single most persuasive content — was hidden from AI systems entirely.

What I value most is that none of this was visible any other way. The site looked great and converted fine. We were failing in a channel we couldn't see into, and we'd have kept failing indefinitely without something checking from the outside."

— Adrian Johnson, DocumentPro

The Takeaway for Other Platform Teams

If your marketing site has never had its raw HTML checked for structured data, FAQ content that only renders on interaction, or identity signals that exist visually but not in markup, it is worth checking before you assume it's fine. The failure mode here is specifically the kind that never shows up in a normal review, because a human looking at the rendered page sees everything working correctly. The gap only shows up when something reads the page the way a crawler or a model does — from the raw markup, top to bottom, with no clicking.

If you're building document intelligence into your own platform and want your extraction API to be equally legible to the engineers evaluating it, DocumentPro's API documentation and MCP server are built the same way we now build our marketing pages — for both humans and the systems reading over their shoulder. Get API access or talk to us about your use case.

Also read: Document AI API: The Developer Guide | Build vs Buy: Document Extraction for Your Platform