DavidGadyan

AEO: 10 Techniques to Be the Answer

Answer Engine Optimization: ten ways to make each section of a page the direct answer that featured snippets, Google AI Overviews and AI assistants pick up.

  1. Structure

    Question headings

    H2 = the question

    When it helps
    Section headings are topic labels ("Pricing", "Integrations"), so nothing on the page matches the way people actually ask.
    What to do
    Write every H2 and H3 as the question a user would ask, under 10 words, one question per section: not "Pricing" but "How much does X cost?".
    Why it works
    Engines use the heading to decide which passage answers which query; a question heading maps straight onto the prompt, and long headings lose match weight.
    Example
    Before: "Our team" After: "Who builds the product?" Before: "Security" After: "How is client data protected?" Before: "FAQ" After: "What do clients ask before hiring?"

  2. Writing

    Answer-first paragraph

    40–75 words, no run-up

    When it helps
    Sections open with background, history or "in this section we will cover…" before the actual answer appears.
    What to do
    Directly under the heading, put a self-contained answer of 40–75 words: the first sentence answers the question, the next two or three add the essential context, everything else moves to a follow-up paragraph.
    Why it works
    Answer engines extract the first self-contained passage under a heading; if that passage is framing, the citation goes to a competitor who leads with the answer.
    Example
    Heading: "How long does onboarding take?" First paragraph: "Onboarding takes two working days: day one imports your data, day two trains the team. Larger accounts add a third day for permissions and SSO." The answer is in sentence one; the rest qualifies it.
    Reported lift
    Cited 3.1× more often than longer passages (published study)

  3. Writing

    One-idea paragraphs

    2–4 sentences each

    When it helps
    A paragraph carries two ideas joined by "but", "however" or "meanwhile", and the model cannot isolate the half that matches.
    What to do
    Split it. One idea per paragraph, two to four sentences, so each paragraph gets its own chance to be extracted whole.
    Why it works
    Extraction happens at paragraph level, not page level: a two-idea paragraph usually gets cut, a one-idea paragraph gets quoted as it is.
    Example
    Before: "The model streams tokens over SSE, which keeps the UI responsive, but the backend also has to buffer them for the audit log, so we use a tee." After: "The model streams tokens over SSE, which keeps the UI responsive." + "The backend tees the same stream into the audit log."

  4. Writing

    Define terms early

    Definition-led blocks

    When it helps
    The page uses a term for ten paragraphs before saying what it means, or calls the same thing by three names.
    What to do
    Open with a one-sentence definition ("X is …"), keep that wording consistent in headings, body and links, and restate the core idea in plain words where it matters.
    Why it works
    Short, definition-led blocks are the ones answer engines lift; consistent, repeated wording raises retrieval confidence and cuts inaccurate summaries.
    Example
    First section: "Generative Engine Optimization (GEO) is the practice of structuring content so that ChatGPT, Perplexity and Gemini cite it." Then "GEO" everywhere after it, never "AI SEO" in one paragraph and "LLM visibility" in the next.

  5. Structure

    FAQ that mirrors real prompts

    Their words, short answers

    When it helps
    Clients and AI assistants keep asking the same five questions and the page answers none of them in one place.
    What to do
    Add an FAQ after the conclusion: the questions phrased the way people type them, each answered in one standalone paragraph of 40–75 words, with FAQPage schema only when the questions are visible on the page.
    Why it works
    FAQ blocks are among the formats models cite most, and every answer competes for the citation on its own.
    Example
    Q: "Can one engineer build the whole AI product instead of a team?" A: "Yes. David Gadyan covers UX, back end, AI, data, DevOps and security end to end, which removes the hand-offs between a designer, an ML team and a DevOps contractor." One paragraph; FAQPage schema because the question is visible on the page.

  6. Structure

    Numbered lists for processes

    Order means ol

    When it helps
    A how-to is written as prose, or the steps sit in bullet points where the order is lost.
    What to do
    Use an ordered list whenever the sequence is part of the answer; keep bullet lists for unordered options and never mix the two.
    Why it works
    Numbered lists tell the model the order matters; they get extracted whole and paraphrased back as steps.
    Example
    Before: "Export the data, then clean it, then load it into the warehouse." After: 1. Export the table to CSV. 2. Remove duplicates and empty rows. 3. Load the file into the warehouse.
    Reported lift
    Cited 2.7× more than plain prose (bullet lists 1.8×) (published study)

  7. Structure

    Comparison tables

    3+ items × 3+ attributes

    When it helps
    Plans, options or tools are compared in paragraphs, with the numbers scattered across the text.
    What to do
    When three or more items are compared on three or more attributes, use a real table, preceded by a one-sentence answer that already contains the key numbers, the currency and the name of the thing.
    Why it works
    A table maps one-to-one onto structured data a model can quote or reformat; prose has to be parsed and rebuilt first.
    Example
    Before: "The Starter plan costs €99 a month with 5 seats, Pro is €399 with 10, and Enterprise is custom." After: "Starter costs €99/month, Pro €399/month, Enterprise is custom." followed by a table with rows Starter, Pro, Enterprise and columns Price, Seats, Prompts.
    Reported lift
    Cited 4.2× more often than the same data in prose (published study)

  8. Structure

    Table of contents and anchors

    Every section reachable

    When it helps
    The answer sits 2,000 words down a long page with no way to link to it directly.
    What to do
    Add a table of contents that links to each H2 by id, and use descriptive anchor text in internal links ("pricing for AI agents", never "click here").
    Why it works
    A table of contents is a structured element engines recognise, and it raises the chance that a single section is surfaced directly in results or AI answers.
    Example
    Top of the page: a list linking to #what-is-geo, #how-llms-extract and #faq, and each H2 carries that id. Internal link text: "the GEO technique map", so the target topic is named in the link itself.

  9. Markup

    Clean semantic HTML

    Real h2, ul, table

    When it helps
    Headings are styled divs, lists are paragraphs with a "•", and the comparison "table" is a CSS grid.
    What to do
    Use real h1/h2/h3, ul/ol/li and table/thead/tbody/th/td; render the important text in the HTML itself; then disable CSS and check the page still reads as headings, lists and tables.
    Why it works
    Crawlers read the markup, not the pixels; a page that collapses into undifferentiated text without CSS cannot be parsed reliably.
    Example
    Before: <div class="h2">Pricing</div> and <p>• 5 seats</p> After: <h2>How much does it cost?</h2> and <ul><li>5 seats</li></ul>. Turn CSS off: the page should still read as headings and lists.

  10. Markup

    Specific title and metadata

    Title, description, schema

    When it helps
    Several pages share a title, descriptions are vague, images have no alt text and the schema promises content that is not on the page.
    What to do
    One specific title per page, an accurate meta description, a canonical URL, descriptive alt text and Article schema that matches the visible content; add FAQPage, HowTo or ItemList only when the page really shows that.
    Why it works
    Metadata cannot rescue a weak page, but it removes ambiguity about topic, author, date and content type, and unsupported schema works against you.
    Example
    Title: "GEO: 11 Techniques to Get Cited by AI | David Gadyan", not "Materials". Description: one sentence naming the topic and the author. Canonical: the EN URL on the EN page, the ES URL on the ES page. Schema: Article with the same headline and dateModified.

Pick a technique on the map to see when it helps, what to do and why it works.

Sources: KIME, "How to Structure Content for LLM Extraction: A GEO Guide for 2026" (Apr 2026), which reports a 2025 analysis of 10,000 AI citations; Victoria Olsina, "Content Structure for SEO and LLMs (2026)" (updated Oct 2026). The citation multipliers are those studies' figures, not measurements on this site.

How do LLMs rank content?

Large language models cite some formats far more than others. Relative citation rate by content format, from the 2025 analysis of 10,000 AI citations reported in KIME's 2026 GEO guide; an unstructured prose paragraph is the 1.0× baseline.

Content formatRelative citation rateBest for
Table4.2×Multi-attribute comparisons, pricing, feature matrices
Answer-first paragraph3.1×Definitional and conceptual questions
Numbered list2.7×Step-by-step processes, ranked recommendations
Bullet list1.8×Feature enumeration, unordered options
Prose paragraph (unstructured)1.0× baselineNarrative or editorial framing

Source: KIME, "How to Structure Content for LLM Extraction: A GEO Guide for 2026" (Apr 2026), reporting a 2025 citation-pattern analysis. Multipliers are relative to unstructured prose on the same data.