--- title: "How to Optimise Owned Content for AI Search | VertoDigital" description: "A practical guide to structuring your owned content so AI engines like ChatGPT, Perplexity, and Google AI Overviews trust, cite, and surface it." url: "https://vertodigital.com/content-hub/blog/how-to-optimize-owned-content-for-ai-search" image: "https://vertodigital.com/images/site/og-default.png" --- # How to optimise your owned content for AI search **Blog · Jun 28, 2026 · 9 min read** By [Teodora Koleva](/content-hub/authors/teodora-koleva), Consultant, SEO & AEO, VertoDigital Buyers are forming their shortlists inside ChatGPT, Perplexity, and Google AI Overviews - before they ever reach your site. Here's how to structure owned content so AI engines trust, cite, and surface it. --- ## Key takeaways - 94% of B2B buying groups now use generative AI for research before talking to sales (Gartner). If you're not cited, you're not in the consideration set. - Write for two audiences at once - the human reader and the LLM. Lead with the answer; cut the fluff. - Structure is the unlock: clean H1→H2→H3 hierarchy, 30–80 word answer blocks, lists, and a real FAQ make content easy for AI to extract. - The technical layer matters: FAQPage and Article schema, semantic HTML, natural-language slugs, descriptive alt text, and visible "last updated" dates. --- ## Why AI search changes the content game Search has fundamentally changed. Large language models like ChatGPT, Copilot, Perplexity, and Claude now act as discovery engines - answering questions directly and shaping the buyer journey before anyone visits your site. Gartner predicts search engine volume will drop by 25% by 2026 as buyers lean on AI assistants, and 94% of B2B buying groups already use generative AI tools for research before they speak to a sales rep. Buyers form their consideration sets during AI-driven research. **If you're not cited, you're not considered** - fewer opportunities, longer sales cycles, missed revenue. The fix is not to abandon SEO. It's to make your content structured, credible, and context-rich enough for AI systems to trust and surface - while staying genuinely useful for the human reader. ## Writing for humans and AI Your content serves two audiences: the human reader and the AI models that summarise information for them. Google still rewards quality, usefulness, and originality, so a human-first approach stays essential. The shift is in how you format it. - **Write for clarity and accessibility.** Plain language, concise sentences (aim for under 20 words). - **Adopt a neutral, authoritative voice.** Be a quotable, credible source, not a sales pitch. - **Write for snippets.** Assume each section will be pulled into an AI answer without its context. - **Use complete, declarative sentences.** "Lead generation campaigns increase qualified opportunities" beats "helps grow pipeline." - **Provide inline context.** Define terms and add examples within the sentence. Avoid overly creative language (skip the metaphors) and don't drop transitional words - connectors like *because*, *therefore*, and *for example* create the logical flow models rely on. ### Optimising for LLMs vs. Google - a balancing act Most practices that improve LLM visibility align with established SEO - structured content, strong E-E-A-T signals, solid technical foundations. But some citation-chasing changes can hurt Google rankings. Watch three traps: over-compressing content (sacrificing depth), neglecting SEO fundamentals (performance, crawlability, canonicals, thin content), and radical site changes (altering URLs or removing pages without redirects). Your ultimate audience is human - any major change for LLMs needs standard SEO hygiene. If the SEO, GEO, and AEO labels themselves are still fuzzy, [here's the difference](/content-hub/blog/difference-between-seo-geo-and-aeo). ## Structure: headings, answer blocks, and lists Clear structure is the single biggest lever for AI extraction. ### Headings and hierarchy Your H1 should communicate a full idea. Use H2s and H3s to break content into sub-topics, and move broad to specific (H1 → H2 → H3). - **Make H1s complete questions or answers.** "How B2B teams generate and qualify leads today" beats "Lead generation." - **Avoid vague headings.** Replace "Overview" or "Best practices" with descriptive titles. - **Maintain a logical narrative.** Headings should read like a story, not loosely related terms. Here's what a clean hierarchy looks like in practice - each level nests logically beneath the one above it: ```

Call to Action

What is a CTA? Examples, key benefits, and measurement strategies

Definition: what is a call to action (CTA)?

CTA examples: different types of calls to action

Different types of CTA formats and designs

Buttons

Contextual links

Banner and video ads

Pop-ups

Slide-ins or carousel ads

Popular types of CTA copy

What are the best practices for writing a call to action

1. Be brief, specific, and actionable

2. Create a sense of urgency

3. Focus on the target audience's goals

4. Make sure the CTA button meets the campaign's objectives

5. Consider the CTA's surrounding marketing copy

Key CTA benefits

Increased leads and conversions

Improved customer engagement

How to measure and test CTA success

CTAs help to boost online marketing success ``` ### Answer-block formatting - don't bury the lead Start each major section with a 30–80 word answer block that directly addresses the question in its H1 or H2. Follow it with deeper explanation, examples, and sources. An optional "Quick answer:" label signals to AI that the block is a direct answer. ### Enhancements for AI extraction - **Use structured lists and tables** - models extract them more reliably than dense paragraphs. - **Number your steps** for how-to content. - **Define key concepts explicitly.** - **Add a real FAQ** with prompt-style questions that mirror how buyers talk to AI. - **Show freshness** - display a "last updated" date, revisit high-value content every 6–12 months, and update the FAQ schema whenever you revise. ## Internal linking Internal links help people and AI understand how your content fits together. - **Use descriptive, keyword-rich anchors** ("See our [LLM visibility measurement framework](/content-hub/blog/seo-aeo-winning-answer-engines)", not "learn more"). - **Link related entity clusters** so connected topics reinforce each other. - **Maintain a hub-and-spoke structure** - pillar pages link to subtopics and back. - **Limit link density** to ~3–5 meaningful internal links per 1,000 words. - **Keep crawl depth shallow** - key pillars no more than two clicks from the homepage. ## The technical side of AI search ### Schema and structured data - **Implement FAQPage or QAPage schema** - the highest-impact markup for LLM discoverability. - **Pair with Article schema** (author, dateModified, headline, about) for credibility and freshness. - **Add Organization or Product schema** with sameAs links to trusted profiles. - **Keep schema and on-page content consistent** - crawlers check that markup matches what's visible. ### Accessibility and semantic markup Use semantic HTML (`
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