Most audits I run end at the same spot: the page is fine, and that's the problem. It ranks, it converts, it has a nav and an FAQ — and AI answers still don't quote it. Getting cited isn't about a better page in general. It's about a page built so a model can lift a clean, self-contained answer out of it. So this is a map: the sections that turn a ranking page into a cited one — what each one does, where it fits, and why a model quotes it.
The problem: ranking and being quoted are two different jobs
When someone asks me how to show up in ChatGPT or AI Overviews, the instinct is almost always to add things — a block, a schema, an “AI section.” That's the wrong end of the problem, so start with why the problem exists at all.
Classic SEO optimises a page to rank. AI Search optimises it to be quoted. Those are not the same job. A model doesn't hand you a position; it builds an answer and lifts the smallest passage that fully answers the query — from whichever source makes that easiest and looks most trustworthy. So the question isn't “what pleases the AI.” It's: if a model were answering my customer's question right now, is there a passage on my page it could quote as-is?
Usually the answer is no. Not because the page is bad, but because the good answer is buried three paragraphs down, wrapped in marketing, split across two sections, and signed by nobody.
The core shift: most sites already have everything they need to rank. What they're missing is a thin second layer that makes them citable. That layer is cheap to build — and almost nobody has it yet.
Two layers, and only one of them is your edge
I split every page into two layers, because it changes where you spend effort.
Layer 1 — the foundation. Title, hero, navigation and breadcrumbs, a body structured with H2/H3, a table of contents, feature or spec breakdowns, related links, a footer. This is the structural, usable, rankable page a competent site already runs. It's necessary. It is also table stakes — having it wins you nothing, because your competitors have it too.
Layer 2 — the citability layer. The sections, and the writing, that make a page a source a model chooses to quote: a direct answer up top, a clear definition, a named and accountable author, sourced numbers, a comparison, a real FAQ. Some are brand-new sections. Some are Layer-1 sections rewritten to be extractable.
The whole game has moved to Layer 2 — not because the foundation stopped mattering (a page that isn't indexed can't be cited), but because the foundation is where everyone is already even, and Layer 2 is where almost nobody is.
First, the four foundation upgrades that cost almost nothing
I'm not going to walk you through titles and footers; if you're reading this, your foundation is fine. But four sections you already own are one small rewrite away from doing real work in AI answers:
- The title and your H2/H3 headings. Turn them into the actual question a person asks. “Pricing” becomes “How much does X cost?” A heading phrased as a query is what a model matches against — and what it can quote as the question above your answer.
- The intro paragraph. It's probably a slow warm-up. Replace the first thing on the page with the answer itself (the Quick Answer, below). A slow intro is the single most common reason a good answer never gets lifted.
- The FAQ. It's probably three generic questions. Rewrite it as real long-tail questions with self-contained answers — each readable with nothing else around it.
- Sources and references. You may have a vague “sources” line. Name them, link them, and lean on your own data where you have it. This is what lets a model cross-check you against things it already trusts.
None of these is a new section. Each is a rewrite — the cheapest citation work there is, and most sites skip it.
The map: the sections that earn citations
Now the layer worth building — the full map. I've grouped the sections by the job they do, with a worked example of each — drawn from my own SEO and AI-Search practice — so you can see the shape, not just the name. You do not add all of them to every page; you pick the ones that fit the page's purpose. Read this as a menu, not a checklist.
Group A — Instant answers and orientation
The passages a model reaches for first, near the top of the page. A Quick Answer / TL;DR is two to four sentences that fully answer the page's core question before any preamble — the single passage most likely to be lifted into an AI Overview. If you add one thing from this whole article, add this one.
Example · Quick Answer
Quick answer
GEO — or AI-visibility — consulting helps a brand get cited in ChatGPT, Perplexity and Google's AI Overviews, not just rank in Google. I work as an independent consultant across 30+ markets, month to month with no lock-in, and I stay honest about what optimisation can and can't do. If you already have an SEO team, I usually come in as an external audit rather than a replacement.
Self-contained, answer-first, quotable without the rest of the page.
A Definition box is one clearly marked sentence defining the core term or entity. “What is X” is one of the highest-volume query types there is — own the sentence a model quotes for it.
Example · Definition box
GEO (Generative Engine Optimisation) is the practice of making a brand's content trustworthy and easy to extract, so that AI answer engines like ChatGPT and Google's AI Overviews cite it in their responses.
An At a Glance / quick-facts panel is a small labelled set of atomic facts — who it's for, key attribute, format, price band. It's effortless to extract for “is X suitable for…” and comparison questions. Key Takeaways — three to five standalone bullet conclusions — do the same job on long pieces.
Example · At a Glance
At a glance
- Best for
- Brands losing visibility to AI answers
- Focus
- SEO + GEO / AI Search
- Markets
- 30+, international
- Engagement
- Month-to-month, no lock-in
- First step
- Free 20-min consultation
Group B — Trust, authorship and evidence
The heaviest lever, and the least glamorous work. This is where citations are actually won or lost. The anchor is a named author — with a named reviewer for high-stakes topics: a real person, photo, credentials, a link. For a model deciding whether to trust a page, accountable, credentialed authorship is the strongest single signal on it. Anonymous content has a ceiling.
Example · Author & reviewer byline
Named, accountable, dated. On YMYL topics you'd add a named subject-matter reviewer beside the author.
Add formalised sources (named, linked, evidence-based — ideally your own data), a visible, honest last-updated date (AI Search favours fresh, maintained content), an expert quote in a named practitioner's own words, and reviews with context — feedback tied to a concrete problem and the outcome, not just stars. One more format punches above its weight here: a single key statistic, sourced, is among the most-quoted things in AI answers.
Example · Key statistic
From audit practice: nowhere does this group bite harder than brand pages for over-the-counter medicines. That's YMYL territory — Google's E-E-A-T bar is at its highest, and AI engines inherit that caution. An anonymous, undated health page with claims and no named sources simply doesn't get quoted, however well it ranks. On those audits, “add a real author, a reviewer, a date, and sourced references” isn't polish — it's the whole difference between being a source and being invisible.
Group C — Decision and depth
The formats models quote out of all proportion to how hard they are to build. A comparison table — X vs Y vs Z across clear criteria — matches one of the most common query patterns and gets cited disproportionately. If your topic has a natural comparison, build the table.
Example · Comparison table
| Independent consultant | Agency | In-house | |
|---|---|---|---|
| Best for | Senior expertise on demand | Scale and many hands | Daily ownership |
| Who does the work | The senior you hired | Often a mixed team | Your own team |
| Cost model | Transparent hourly | Retainer + margin | Salary + overhead |
| Lock-in | None, month-to-month | Often 6–12 months | Permanent hire |
The other depth formats share the same trait — scannable, self-contained, lifted cleanly. Do's and Don'ts maps onto “what's the right way to…”; Myth vs Fact onto “is it true that…”; a decision guide (“which is right for me”) onto “what should I use for…”; and a mechanism explainer (“how X works,” in plain language) onto “how does X work.”
Example · Do's & Don'ts
Do
- Lead each page with a direct answer
- Put a named author on expert content
- Earn mentions on sources AI already trusts
Don't
- Chase a “ChatGPT hack”
- Mass-produce thin AI pages
- Guarantee specific rankings or citations
Group D — Guided and interactive
Sections that answer process and “how do I…” questions competitors rarely address. A step-by-step how-to — numbered and self-contained — is the native format for “how do I…” answers and voice assistants.
Example · Step-by-step
- Ask the models. Put your category and your comparisons to ChatGPT and Perplexity, and see who they cite today.
- Fix the entity. Consistent About and author pages, the same brand name and description everywhere.
- Add answer-first sections. Quick Answers and real FAQs on your key pages.
- Build off-site trust. Digital PR and mentions on the sources AI already leans on.
A checklist / self-check maps onto “how do I know if…” and keeps a reader on the page; a what-to-expect / timeline answers “how long does X take,” a question competitors rarely address; and a People Also Ask / FAQ — four to eight real questions with concise, self-contained answers at the foot — is the highest-leverage section almost every page can carry. (This article's own FAQ, below, is that format in use.)
Example · Self-check
- You show up when you ask ChatGPT or Perplexity about your category.
- Your key pages answer the question in the first screen.
- Your expert content is signed by a named author and a date.
- You're mentioned on external sites AI already trusts.
How you write each section matters more than which ones you add
You can add every block on that map and still not get quoted, because extractability is mostly about how each section is written. Five rules I apply to every one:
- Answer first, elaborate after. Open each section with the conclusion. Never make the model dig for it — it won't.
- One idea per section. Keep each block self-contained, so it can be cited without the surrounding page for context.
- Headings as questions. Phrase H2/H3 the way people actually search and ask.
- Plain, direct language. Short sentences, short paragraphs, entities defined on first use. Marketing prose is hard to quote; plain statements are easy.
- Original insight and data. First-hand experience and unique numbers are exactly what models prefer to cite, because nobody else has them.
These aren't a section you add. They're the difference between a page with all the right blocks that still doesn't get quoted, and one that does.
Where this gets over-engineered — an honest note from audits
The failure mode I see on sites that have heard about all this is the opposite one: every block bolted onto every page. It reads worse for humans and it doesn't help. A few things I flag regularly:
- Not every section belongs on every page. A definition box on a page that isn't about a concept, a comparison table where there's nothing to compare — these are noise. Match the section to the page's job; that's why the map is a menu, not a checklist.
- Schema without backing. Marking up an FAQ or an author that isn't really on the page. Models check whether what you declare is actually there; declaring and not delivering works against you.
- Blocks instead of substance. All the right sections, filled with thin, generic text. The formats help a model find your answer. They can't make a weak answer worth quoting.
Citability is a thin layer on top of a page that already says something true and useful. It is not a substitute for having something to say.
A quick coverage check
Run any page or article past this:
- Foundation in place — title, structure, navigation, related links, footer.
- A direct answer up top — Quick Answer / TL;DR before anything else.
- Authorship visible — named author, a reviewer for high-stakes topics, and a last-updated date.
- Question-based headings, each opening with its answer.
- At least one depth block — comparison, do's & don'ts, steps, a sourced stat — where it fits.
- A real FAQ / People Also Ask with genuine long-tail questions.
- Named, linked sources; your own data where you have it.
- Every section stands alone as a citable answer.
If a page clears that list, it's built the way AI Search rewards. And most of the work isn't adding sections — it's rewriting the ones you already have so a model can quote them. If you want that done across your key pages as one coherent piece of work, that's what GEO / AI visibility is; and if the acronyms blur together, I untangle them in SEO, GEO, AEO and LLMO.
FAQ
Frequently asked questions
No — and you shouldn't. The map is a menu, not a checklist. Match sections to the page's job: a comparison table where there's something to compare, a definition box on a concept page, a Quick Answer and an FAQ almost everywhere. A page with every block bolted on reads worse and doesn't get cited more.
A Quick Answer or TL;DR near the top — two to four sentences that fully answer the page's core question before any preamble. It's the passage most likely to be lifted into an AI answer, and almost no site has it.
No. A page that isn't indexed and doesn't rank has nothing for a model to pull — AI answers lean heavily on the search index underneath. The foundation still matters; it's just no longer where the advantage is. Citability is a layer on top of solid SEO, not a replacement for it.
It's one of the strongest signals on the page, and it matters most on YMYL topics like health and finance, where the trust bar is highest. A named, credentialed, consistent author — plus a reviewer for high-stakes content — gives a model a reason to trust you; anonymous “admin” content has a ceiling.
No. Schema helps a model find and understand what's already on the page — it's the floor, not a lever. Marking up an answer or author that isn't really there works against you, because models check.
A good article and a citable one overlap, but a citable page also puts the answer where a model looks first, keeps each section self-contained, signs it with a real author and date, and backs claims with named sources. Same substance, arranged so a passage can be lifted out cleanly.
