AEO vs. GEO vs. SEO

AEO vs. GEO vs. SEO (What Each Actually Covers—and How They Fit Together)

SEO helps you earn visibility in traditional ranked results. AEO tunes content so assistants and “answer engines” can lift and cite it directly. GEO addresses the newer class of generative engines (e.g., Copilot Search, Perplexity, Gemini experiences) that synthesize across sources—optimizing how, when, and why you’re cited inside composed answers. In practice, AEO/GEO are subsets of AI Relations: they’re presentation and availability hygiene that support your larger objective—becoming the safest source a model can trust. 

Working definitions (plain-English, buyer-friendly)

SEO

Optimize sites and pages so web search engines index, understand, and rank them for queries—technical health, content quality, intent match, links, and structured data. It’s about earning positions on results pages. 

AEO (Answer Engine Optimization)

Structure content to be directly answerable and citable by answer engines and AI features (snippets, voice assistants, chat surfaces). Think: question-led sections, tight definitions, FAQs, data points, and clarity the assistant can quote. 

GEO (Generative Engine Optimization)

Optimize for systems that synthesize answers from multiple sources and show inline citations. Academic work formalizes this and shows visibility gains when you design content for model-scannability and justification (citations, stats, quotes). 

Why this matters now

AI assistants increasingly ground responses in web results and show sources inline (e.g., Copilot Search uses Bing results and additional reformulated queries to assemble an answer with cited links). You don’t “rank” in one slot—you’re chosen as supporting evidence across many prompts. 

The quick compare

User experience target

• SEO → ranked lists of links.

• AEO → direct answers/snippets/AI overviews that quote you.

• GEO → multi-source, citation-rich synthesized answers where you want consistent inclusion. 

Primary levers

• SEO → crawlability, internal linking, intent-matched pages, links, schema.

• AEO → question-first layout, definitional copy, concise tables, FAQs, eligibility/steps, JSON-LD where relevant. 

• GEO → evidence density (stats, quotes, citations), clarity over flourish, consistent claims across owned and earned sources. Formal studies find up to ~40% visibility lift from such tactics in generative engines. 

How engines pick sources

• SEO → classic ranking signals.

• AEO/GEO → “is this page the cleanest way to justify the assistant’s statement?” (coverage, corroboration, freshness). Perplexity, for example, emphasizes cited, real-time sourced answers. 

When to emphasize each

Lead capture via non-AI search remains large → keep a strong SEO baseline (crawlable architecture, canonical reference pages, schema). 

Your buyers are asking assistants complex questions → layer AEO patterns: FAQs per intent, definitional sections, eligibility matrices, and short, citable paragraphs that resolve common prompts in your category. 

Your category is frequently summarized by AI → invest in GEO: increase evidence density and alignment across owned pages and third-party confirmations so generative engines can comfortably cite you across paraphrases and versions. (Academic GEO work shows measurable visibility gains from citation-friendly composition.) 

Tactics checklist (without the fluff)

For SEO (foundation)

• Crawlable IA, fast pages, canonical tags, internal links from hubs to subpages.

• Structured data in JSON-LD where applicable (FAQ, HowTo, Article, Product, etc.). 

For AEO (answer surfaces)

• Rewrite headers as the question a user would ask; answer in 2–4 tight sentences, then expand.

• Use definition boxes, comparison tables, and step lists that can be lifted verbatim.

• Maintain up-to-date FAQs per product and use cases; keep claim wording consistent across pages. 

For GEO

• Add justifications: stats with sources, short quotations, and explicit citations on your canon pages.

• Align owned claims with earned mentions (trade press, standards bodies, respected directories). Studies indicate generative engines reward corroboration and clear attributions. 

• Make facts machine-legible (tables, changelogs, versioned documents) and keep them fresh.

Measurement (treat it like PR, not rank-watching)

Don’t chase a single “position.” Track inclusion and framing across engines and prompts, plus second-order impact. Concretely:

• Inclusion: how often your pages (and which statements) are cited in answers.

• Framing: how assistants describe you vs. competitors (features, fit, caveats).

• Corroboration: growth of accurate third-party mentions that assistants tend to trust.

• Demand signals: branded search, direct traffic lift, “Referred by ChatGPT/Copilot” notes in CRM.

This triangulation mindset mirrors modern PR guidance around earning your way into AI-generated answers via credible sources. 

Where AEO/GEO live inside AI Relations

AEO and GEO are tactics inside your AI Relations program. They make your content easy to lift and justify; your AI Relations work makes your brand easy to trust (reference architecture, authority building, and the referral path). For the strategic pieces, see:

• How LLMs Evaluate Brands (/ai-relations/how-llms-evaluate-brands/)

• Building AI Brand Authority (/ai-relations/brand-authority/)

• AI Company Wiki / Reference Manual (/ai-relations/brand-wiki/)

• The AI Referral Engine (/ai-relations/ai-referral-engine/)

Platform notes (today’s reality)

• Copilot Search (Bing) grounds answers on Bing results and additional queries it issues on the user’s behalf, then shows sources—optimize for clarity and corroboration, not just keywords. 

• Perplexity markets “answers with sources/citations” as a core feature; concise, source-rich pages and credible third-party coverage improve your odds of being referenced. 

• Google continues to rely on structured data for rich experiences; JSON-LD is the recommended format when feasible. 

• Academic GEO research (KDD 2024) formalizes generative engines (retrieval + multiple LLM steps) and shows visibility improvements when content is engineered for citation and justification. 

What to do next

1. Stabilize SEO fundamentals (crawl, IA, JSON-LD where relevant). 

2. Refactor priority pages for AEO (Q&A headers, short definitional blurbs, eligibility/pricing tables). 

3. Upgrade canon for GEO (add stats/quotes with sources; align claims with earned coverage). 

4. Run PR-style programs to earn corroboration in outlets assistants favor. 

5. Monitor like PR (inclusion, framing, corroboration, demand), and iterate.

Sources & further reading

• Google Search Central, Intro to structured data (JSON-LD recommended). 

• Microsoft, Copilot Search overview (grounded on Bing results and additional queries). 

• Microsoft Learn, How web search grounding works in Microsoft 365 Copilot. 

• Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024). 

• CXL, AEO: The Comprehensive Guide (industry definition). 

• Search Engine Land, AEO landscape and players (industry overview).