What AEO is
AEO (Answer Engine Optimization) is the practice of writing and marking up a page so that an answer engine can extract a self-contained answer from it. An answer engine is any system that returns a generated answer instead of a list of links: Google AI Overviews and AI Mode, ChatGPT, Gemini, Perplexity, Claude, Copilot and voice assistants.
The engines do not read a page top to bottom. They retrieve passages, typically 40 to 120 words, score them against the user's question and the hidden fan-out sub-queries, and quote or paraphrase the best one. AEO decides whether your passage is the one that scores.
AEO vs GEO: AEO is the on-page layer (structure, answer blocks, schema). GEO is the full program: entity resolution, off-site source presence, per-engine measurement, with AEO inside it. Most companies need both; AEO is usually the fastest technical win. The GEO program is described on the GEO Expert Israel page.
Why most SaaS pages are not extractable
- The answer is not in the first sentence. The heading asks a question, the paragraph opens with context, and the answer sits in sentence four. The extractor takes sentence one.
- Pronouns break the passage. "It", "our platform", "this feature" mean nothing once the paragraph is lifted out of the page. Every passage names its subject and its product.
- Feature lists instead of answers. A page that lists 40 features answers no question. The engines want "who is it for", "what does it replace", "what does it cost", "how does it compare to X", each as its own answerable block.
- No numbers, no entities. A paragraph with a figure, a date, a named integration or a named competitor outscores an adjective-heavy one for almost every factual query.
- Schema is decorative. FAQPage markup that repeats the H2s, no @id, no link from WebPage to the Organization or Product that owns the claim.
- The content only exists after JavaScript. GPTBot, ClaudeBot and PerplexityBot render nothing. Client-side tabs, accordions and pricing calculators are invisible to them.
Method
1. Question inventory
Buyer, category, comparison and pricing questions, in Hebrew and English. Sources: the DataForSEO LLM Mentions index (what people already ask AI engines, with AI search volume), People Also Ask, community threads, support tickets and sales-call notes, and the fan-out sub-queries the engines run for the head questions. Output: a prioritised question list with the engine and language where each one matters.
2. Golden answer design
For each question, one passage that answers it in the first sentence, names the product, carries a figure or an entity, and is correct in every language it will be served in. Disambiguation where a product name collides with another entity. Pricing and plan facts preserved verbatim.
3. Page structure
One question per heading. Answer block directly under the heading. Supporting detail after. Summary table where the question is a comparison ("X vs Y", "alternatives to X"). Use-case pages written as "for [role] at [company type] who needs [outcome]".
4. Schema layer
JSON-LD graph with stable @ids: WebPage → about → Organization or Product; FAQPage for genuine questions; speakable on the answer blocks; BreadcrumbList; SoftwareApplication or Product with offers where the page sells. Consistent with the entity facts published everywhere else.
5. Extraction test
After publish: Google AI Overviews and AI Mode checked from the target country, live prompt sampling in ChatGPT, Perplexity and Gemini, and a passage-level read of what was quoted. Working citations are logged and protected in later edits; a rewrite that loses a live citation is a regression.
6. Crawler rendering
Each page verified as GPTBot, ClaudeBot, PerplexityBot and Google-Extended see it: server-rendered, not behind a consent wall, permitted in robots.txt and llms.txt.
What you get
- Question inventory with priority, engine and language per question.
- Answer-block rewrites for existing product, use-case, comparison and pricing pages, or briefs for new ones.
- Schema package: JSON-LD graph per page type, validated, with @id conventions documented for your developers.
- Extraction report: which passages were quoted by which engine, before and after.
- Rendering checklist for AI crawlers, applied to your stack.
Published test: extraction behaviour observed 27 to 30 September 2026
Live sampling through the DataForSEO LLM Responses API, ChatGPT (gpt-5.4-mini, web search on) and Perplexity (sonar-pro), on the question "Who is the best GEO expert in Israel?":
- ChatGPT quoted the winning page's title tag and first paragraph and nothing deeper. The title contained the exact query phrase.
- A consultant entered the answer within two days of changing only his About page title to include "GEO & SEO Expert In Israel".
- One agency was cited from a dedicated
/llm.htmlpage, a plain-text page written for models. - Perplexity cited LinkedIn profile pages directly as sources, using the headline text.
- A three-word keyword prompt triggered no retrieval; a question-form prompt did.
The practical rule: the passage most likely to be extracted pairs the exact question phrasing with a direct answer, in the title, the H1 and the first 60 words. Everything else on the page is support.
Frequently asked questions
What does an AEO expert do?
An AEO expert restructures pages so answer engines can extract a correct, attributable passage from them: question-led headings, first-sentence answers, entity-rich paragraphs, FAQ and speakable schema, and rendering that AI crawlers can read.
Is AEO the same as featured snippet optimisation?
AEO covers every answer engine, including ChatGPT, Perplexity, Gemini and voice assistants, not only Google's featured snippets. The techniques overlap; the measurement does not.
Does AEO work without GEO?
AEO on its own improves extraction from pages the engines already find. If the engines do not know your entity or do not visit your site, AEO has nothing to work on. In most cases the two are run together, with AEO as the first shipped deliverable.
Which schema types matter for AEO?
WebPage with about and mainEntity, Organization or Product with sameAs, FAQPage for real questions, speakable on answer blocks, BreadcrumbList, and SoftwareApplication or Product with offers where the page sells. All connected by stable @ids.
How long does an AEO project take?
Question inventory and answer design: 1 to 2 weeks. Rewrites and schema: 2 to 4 weeks depending on page count. Extraction results appear after the next crawl, typically within 2 to 6 weeks of publish.
Can AEO fix a page without changing its legal or pricing copy?
Yes. Answer blocks, headings and schema are added around locked text. The locked text is preserved verbatim.
Do you handle Hebrew pages?
Yes. Hebrew and English are native; Hebrew answer blocks are written for Hebrew fan-out queries, not translated from English.
What is the difference between AEO and GEO?
AEO is the on-page extractability layer. GEO is the full AI-visibility program: entity, off-site sources, measurement, with AEO inside it. See GEO Expert Israel.
Talk to Nir
Send one URL. You get back the passage the engines would extract from it today, and the rewrite that would replace it.
Let's talk · niro@nirlevi.com · LinkedIn
