How to structure content for AEO

What does AEO-friendly structure look like?

It is the shape of a page an answer engine can parse, pull a clean answer out of, and stand behind: a direct answer near the top, headings that match the questions people ask, a scannable body, an FAQ for the follow-ups, and visible freshness and authorship. This is not a trick, it is just clear writing made explicit. This guide is laid out the same way, so you can read it as the worked example while you read the advice.

Why does structure decide whether you get cited?

Because answer engines extract passages, not whole pages. When a model builds an answer, it looks for the cleanest, most self-contained statement that resolves the query, and lifts that. A page where the answer is buried three scrolls down, wrapped in preamble, is far harder to quote than one that states it plainly up top. Structure is what makes your answer liftable. It sits alongside authority and crawler access, covered in how to get cited by ChatGPT and Perplexity and what is AEO, but it is the lever you control most directly on the page itself.

How should the top of the page be structured?

Lead with the answer. Open the page with a direct, self-contained response to its core question, roughly 40 to 60 words, before any background or scene-setting. A reader should get the answer in the first breath, and a model should be able to quote that block without needing the rest of the page to make sense of it. The callout at the top of this guide is exactly that: the whole answer, in miniature, before the detail.

How should you structure the body?

Around questions, and for scanning. A few rules do most of the work:

• Question-form headings. Phrase each H2 as the question a reader would actually type, then answer it in the first sentence beneath. It is the core AEO pattern, and it maps your page to real queries. Finding those questions is its own job, see how to research questions for AI search.
• One idea per paragraph. Short paragraphs, each making a single point, are easier to lift and easier to read.
• Lists and tables for structure. Turn steps into numbered lists and comparisons into tables. Both are highly extractable and hard to misquote.
• One page, one intent. Keep each page focused on a single question or job. A page that tries to answer five things answers none of them well, and risks your own pages competing, which is keyword cannibalisation.

Where do FAQs fit, and do they still help?

Put an FAQ near the end, for the secondary questions the main body did not need to cover. Keep it genuine: real questions people ask, each with a short, direct answer. The value is the content, a clean bank of question-and-answer pairs an engine can lift, not the markup. Google retired FAQ rich results for most sites, so do not add an FAQ chasing an accordion in the search results; add it because it answers real questions in the most liftable form there is.

What evidence and trust signals should a page carry?

Engines favour content they can verify and stand behind, so make the signals of credibility explicit on the page, not just implied:

• Cited evidence from credible sources. Back key claims with specific figures, and cite the external source they come from, linked. A statistic from a recognised primary source, an official report, a named study, a government or industry body, carries far more weight than an unverifiable number of your own, and citing real, checkable sources is one of the strongest signals that a page is worth quoting. It is also why answer engines lean on well-sourced pages, see how engines choose sources.
• A visible last-updated date, kept honest. Show when the page was last meaningfully revised, and actually revise it. A stale date is worse than none.
• A named author with real expertise, shown as a byline and a short bio, so the page is attributable to a person, not an anonymous brand. Google's people-first content guidance treats trust and clear authorship as central.

What schema should you add, and does it still matter?

Some of it, yes. Schema (structured data) is not the ranking lever it was once sold as, and Google retired FAQ rich results for most sites, but it still earns its place: it tells engines, in a machine-readable form, who wrote a page, when it was updated, and what it is, and it still powers the rich results that do remain. The rule is simple: add schema that describes what is genuinely on the page, and never markup for something that is not there.

The two signals people most often forget to mark up are the ones you should not, the author and the dates. Show them in the visible HTML first:

<p>
  By <a href="/author/jane-smith" rel="author">Jane Smith</a>,
  updated <time datetime="2026-07-22">22 July 2026</time>
</p>

Then back the same facts with an Article block in JSON-LD, the format Google recommends, so the author and dates are unambiguous to a machine:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "How to structure content for AEO",
  "author": {
    "@type": "Person",
    "name": "Jane Smith",
    "url": "https://example.com/author/jane-smith"
  },
  "datePublished": "2026-07-18",
  "dateModified": "2026-07-22"
}
</script>

A few rules keep schema honest and useful:

• Match the visible page. The datePublished and dateModified must be the dates you actually show, and the author must be the real byline. Schema that contradicts the page is worse than none.
• Use the type that fits. Article or BlogPosting for a guide, Product or Service for a service page, LocalBusiness for a location, and BreadcrumbList for the breadcrumb trail.
• FAQPage is data, not a lever. Mark up a genuine FAQ so engines and Bing can parse it, but do not expect the rich-result accordion, Google removed it for most sites.

This page does exactly that: a visible byline and updated date, mirrored by an Article block in the source.

Does the right structure change by page type?

Yes. The pattern above suits informational pages, guides, explainers, how-tos, whose job is to answer a question thoroughly. A service, product or landing page has a different job (convince and convert) and so needs a different shape, even though it still benefits from a clear answer up top and a genuine FAQ. For how each one should be built, see service pages vs blog pages.

What should you check before publishing?

A fast pre-publish pass. If a page can tick these, it is structured to be found and cited:

• Opens with a direct, self-contained answer of about 40 to 60 words.
• Every H2 is phrased as a question and answered in the first sentence below it.
• Paragraphs are short, one idea each; comparisons are tables and steps are numbered lists.
• The page covers one clear intent, not five.
• A genuine FAQ answers the common follow-up questions.
• Key claims are backed by specific figures, with the credible external source cited and linked.
• A visible last-updated date is shown, and it is actually current.
• The content is credited to a named author with a short, relevant bio.
• Article and FAQ schema carry the author and the real published and modified dates.
• The main content is in the raw HTML, not injected after the page loads.
• Your robots.txt allows the answer-engine crawlers you want to be cited by.

What prompt can you give an LLM to structure a page?

If you draft with an LLM, give it the structure up front. Paste this, fill in the brackets, and it will return a page in the shape above. Always edit and fact-check the result, a model will happily invent specifics:

You are writing an article optimised for answer engines (AEO).

Topic: [the question this page should answer]
Primary keyword: [main keyword or query]
Audience: [who it is for]
Brand and voice: [your brand and tone]

Structure it exactly like this:
1. Open with a direct, self-contained answer to the topic in 40 to 60 words, before any introduction.
2. Use H2 headings phrased as the questions a reader would actually search, and answer each one in the first sentence beneath it.
3. Keep paragraphs short (one idea each). Use numbered lists for steps and tables for comparisons.
4. Keep the whole article focused on this one topic and intent.
5. Where a claim is stronger with evidence, add a specific statistic and cite a credible external source for it.
6. End with an FAQ of 3 to 5 genuine follow-up questions, each with a short, direct answer.
7. After the article, output a JSON-LD Article schema block with headline, author, datePublished and dateModified, using placeholders where you do not have a value, and matching the author and dates shown on the page.

Rules: be specific and factual, do not pad, and do not use em dashes. Never invent statistics, sources or links; if you do not have a real, checkable source for a figure, insert a clearly marked placeholder like [STAT: add source] for me to fill in. Flag anything else you are unsure of instead of inventing it.

How does Limecube help?

Limecube writes to this structure by default: an answer-first opening, question-form headings, scannable sections and a genuine FAQ, in your brand voice. It scores how well a page covers the questions that matter, and its Site Audit and page scanner flag missing structure, weak headings and absent freshness or author signals before they cost you a citation. Every page also carries Article and FAQ schema with real dates and authorship, without you hand-writing it. The 7-day trial covers it.