What is Answer Engine Optimization (AEO)?
Answer Engine Optimization (AEO) is the practice of structuring content and building authority so that answer engines — Google AI Overviews and AI Mode, ChatGPT, Perplexity, Gemini, Copilot, voice assistants, and featured snippets — return your brand as the answer. Where classic SEO competes for ranked links, AEO competes for being quoted, named, or recommended inside the answer itself. It builds on SEO rather than replacing it: engines retrieve from search indexes first, then select which passages to cite. AEO makes your passages the most extractable, verifiable, and trusted candidates in that selection.
A common mistake is writing a 40–60 word answer capsule that restates the question instead of answering it directly in the first sentence. A practical test: read only the first sentence after any heading — if it alone answers the question without the rest of the paragraph, the capsule is doing its job; if it needs the following sentences, rewrite it.
What is the difference between AEO and GEO?
AEO (Answer Engine Optimization) is the broader discipline: winning any surface that delivers an answer instead of a link list, including featured snippets, People Also Ask, knowledge panels, and voice assistants. GEO (Generative Engine Optimization) is the subset focused on AI-generated answers from large language models like ChatGPT, Perplexity, and Google AI Overviews. In practice the tactics overlap almost entirely — answer-first structure, evidence density, entity authority, and off-site mentions win both — so most practitioners, including us, treat them as one job. Our dedicated GEO service goes deeper on LLM-specific citation mechanics.
A practical decision rule for deciding where to invest: audit your current featured-snippet and People-Also-Ask coverage first, since those legacy answer surfaces still feed voice assistants and often predict which pages will also earn AI Overview citations. Pages already winning a featured snippet are frequently the cheapest wins to extend into full AEO coverage, because the extractable structure already exists.
How much do AEO services cost?
AEO services at Meek Media run $2,000–$8,000 per month depending on content volume, number of engines tracked, and off-site mention work. A one-time AI Visibility Audit — baseline citation share across ChatGPT, Perplexity, and AI Overviews plus a prioritized roadmap — costs $1,500–$3,000. The market is young and pricing is erratic: some agencies relabel standard SEO as "AEO" at a premium, while enterprise GEO platforms charge $500+/month for tracking alone with no execution. We price production and measurement together, so you pay for citations earned, not dashboards.
A common mistake is quoting AEO work at classic SEO retainer pricing without separating out prompt-tracking cost, which can meaningfully change the total. A practical rule: ask any provider to break out content production, entity and schema work, and measurement as line items — bundled pricing without that breakdown makes it impossible to tell whether tracking is genuine or an afterthought tacked onto existing SEO deliverables.
How do answer engines decide which sources to cite?
Each engine runs retrieval-augmented generation: it retrieves candidate pages from an index, reranks them, then cites a small subset — ChatGPT cites only around 15% of the pages it retrieves, and Perplexity cites 3–4 sources from 60+ candidates. Selection favors passages that directly answer the query near the top of the page, contain specific statistics and attributed quotes (the Princeton GEO study measured +30–40% visibility lifts from these), load fast, and come from sources with broad topical authority and third-party validation. Keyword stuffing measurably backfires. AEO is the discipline of winning each stage of that pipeline deliberately.
A practical check worth running before investing further: search a handful of your buyer's real questions in ChatGPT and Perplexity yourself and note whether the cited sources are pages you control or third-party ones. According to the retrieval mechanics involved, if third-party sources dominate your category's answers, off-site mention work will likely outperform more on-site content in the near term.
Does schema markup help with AEO?
Partly, and it is important to be precise about where. Third-party LLMs like ChatGPT and Perplexity read your visible HTML, not your JSON-LD — tests show facts placed only in schema are not extracted, and causal studies find near-zero citation lift from adding schema alone. Where schema genuinely matters: Google's own AI Overviews and AI Mode consume structured data at runtime, and Organization sameAs graphs anchor your brand as a verifiable entity in knowledge graphs that flow into model training data. So we implement schema as entity hygiene and Google-first-party fuel, while putting every fact we want cited in visible body text.
A common mistake is treating schema markup as a citation shortcut for third-party LLMs, when the visible body text is what those engines actually read and extract. A practical rule: write every fact you want cited in plain paragraph text first, then add schema as a separate layer for Google's own AI surfaces — never let schema substitute for the visible answer itself.
