An answer engine optimization agency rebuilds your pages so answer engines can extract, attribute and reuse what you publish. The work is technical: question led page structure, standalone answer blocks, Organization and Product structured data, consistent entity facts across every profile that names you, and verified crawler access for AI user agents. It is engineering on the page, not a ranking service.
That definition sounds narrow, and it is meant to. The loose version of this category promises AI visibility and delivers a content calendar. The technical version has a checklist you can audit, which is the version worth paying for. If the surrounding vocabulary is still fuzzy, start with LLMO versus SEO versus GEO versus AEO. DevCommX ships this work as engineering, so what follows is the actual change list, the schema that matters in 2026 rather than the schema that mattered in 2021, and the one promise nobody can honestly make.
The short answer: what an answer engine optimization agency does
An answer engine optimization agency changes four things: how your pages are structured, what machine readable facts they carry, how consistently your brand is described everywhere else, and whether AI crawlers can reach the result. Everything else in a proposal is either a means to one of those four or padding. Our AEO services are scoped that way, and you should ask any provider to map their line items onto the same four.
It helps to know what the platforms themselves say, because it is less exotic than most decks imply. Google's guide to optimizing for generative AI features on Search states that standard SEO best practice still applies and that there are no additional requirements or special optimisations to appear in AI Overviews or AI Mode, beyond content that is crawlable and useful. Read honestly, that is not a reason to skip the work. It is a reason to be suspicious of anyone selling a secret.
So what you are buying from answer engine optimization services is disciplined execution of unglamorous things: clean structure, accurate markup, one consistent set of facts, and unblocked access. Those are auditable. That is the point.
AEO and GEO, settled in one section
The two terms describe different altitudes of the same problem. AEO operates on a page and a question: can a machine lift a correct, self contained answer from this page and attribute it to you. GEO operates on a brand and a category: when a model composes a recommendation, are you in it and described correctly. A useful rule is that AEO is something you can finish on a page, and GEO is something you can only influence over a category.
The practical consequence is sequencing. AEO work is largely within your control, so it goes first. The brand level work, which depends on third party sources you do not own, runs longer and is the subject of its own discipline, covered in AEO versus GEO and in what LLMO actually means. This post stays on the technical surface.
| Dimension | AEO | GEO |
|---|---|---|
| What it optimises | One extractable answer to one specific question | The whole generated response and which brands it names |
| Typical surface | AI Overviews, featured snippets, assistant direct answers, voice | ChatGPT, Perplexity, Gemini and Copilot conversations |
| Main lever | Page structure, schema and entity clarity | Content plus off site mentions and source authority |
| Unit of work | A page, or a single buyer question | A brand inside a whole category |
| Evidence it worked | Your wording shows up in the answer, attributed to you | Your brand is named and described correctly |
| Main failure mode | The answer is lifted but credited to someone else | The model keeps recommending sources it trusts more |
| Shared prerequisite | Crawlable, unambiguous, internally consistent content | Crawlable, unambiguous, internally consistent content |
One row deserves emphasis. The AEO failure mode is having your answer used without attribution, which is why entity clarity and markup are not decoration. If a machine can lift your sentence but cannot reliably tell whose sentence it is, you have done the hard half of the work and skipped the cheap half.
The four things an answer engine optimization agency changes on your site
One, question led structure. Headings become the questions buyers type, in their words rather than your category's jargon, and each one is followed immediately by the answer instead of three paragraphs of preamble. Two, the standalone answer block. The first 40 to 70 words under a question heading must make sense with no surrounding context: a complete sentence, the subject named rather than pronouned, no it depends, no cross reference to an earlier section. This is the highest leverage edit in the whole discipline, and the playbook version of it is in how to optimise content for LLMs.
Three, structured data and entity facts. Covered in detail in the next section, because it is where most audits are wrong. Four, retrieval access and rendering. If your key content only exists after client side JavaScript executes, or a firewall rule blocks a named AI user agent, none of the above matters. Google also documents the controls that suppress your content in AI experiences, and site owners trip them by accident: the nosnippet, data-nosnippet and max-snippet directives all limit what Search can display, including in AI formats. A legacy max-snippet value set years ago to control a snippet is a common self inflicted wound.
Commercial pages need the same treatment and usually get skipped because they read as sales assets rather than content. Pricing is the clearest example, and it is worth its own pass, which we set out in optimising pricing pages for AI search. A model asked what something costs will answer from whatever page states it plainly, and that page is frequently a competitor's comparison post rather than yours.
Schema, entities and the extractable answer
Start with what schema is no longer for. Google restricted FAQ rich results to well known, authoritative government and health sites in August 2023, and Google retired the FAQ rich result in May 2026 and has since removed the FAQPage documentation entirely, so FAQ markup no longer earns a rich result. FAQPage is still a valid schema.org type and leaving it in place harms nothing, but any AEO agency still pitching FAQ schema as a visibility feature is working from a 2021 playbook.
What schema is for is disambiguation. An answer engine has to resolve which company you are before it can attribute anything to you, and that resolution is easier when Organization markup carries your legal name, your logo, and sameAs links to the profiles that corroborate you. Product, Article and BreadcrumbList do similar work for the rest of the page. None of this makes a model cite you. It makes you unambiguous once it decides to.
There is a hard constraint that catches teams who treat markup as a growth hack. Google's general structured data guidelines require that markup represent the main content of the page and not describe content invisible to the user, with manual action as the penalty. Marking up an answer you did not publish is not clever, it is a policy breach.
Entity consistency is the quieter half and the one that produces the strangest bugs. Your site says one company name, your LinkedIn says a slightly different one, an old directory listing carries a former product name, and a review platform describes you as a category you left two years ago. A machine reading all four has to pick, and it will sometimes pick the wrong one. The fix is unglamorous: one canonical fact set, written down, then propagated everywhere it appears and rechecked on a schedule. This is the part no tool does for you.
What the first 90 days look like
Days 0 to 30, audit and baseline. Crawl the site as an AI user agent would, list which priority pages render server side, validate existing structured data against what is visible, and pull the canonical fact set out of whatever is currently the most accurate source. In parallel, record how assistants answer a fixed set of buyer questions today, so month three has something to compare against.
Days 31 to 60, ship. Restructure the priority pages into question led sections with standalone answers. Fix the schema, including removing markup that no longer earns anything and adding Organization and Product where it is missing. Clear the access blockers found in the audit. This stage is mostly engineering tickets, and it should be trackable in your own backlog rather than in an agency dashboard.
Days 61 to 90, re-measure and correct. Re-run the question set, compare answers, and look specifically at attribution: when your wording appears, are you named. Assistants differ enough that this is worth doing per platform rather than in aggregate, and the per platform detail for one of the harder ones is in how to get cited by Perplexity in B2B. Ninety days is enough to prove your pages are extractable. It is not enough to prove a revenue effect, and a credible agency will say so.
Measuring AEO without a rank tracker
There is no position one in a generated answer, so rank tracking does not translate. Three measurements replace it. First, extractability, which you can assess directly: for each priority question, does the page contain a self contained answer a machine could lift, and is the entity named inside it. This is the only one of the three you fully control, and it is worth scoring page by page.
Second, first party platform data. Google added generative AI performance reports to Search Console, giving site owners a dedicated view of impressions inside AI experiences on Search. Third, assistant referral behaviour in your own analytics, which needs the referrers grouped deliberately before the numbers mean anything, a setup we document in tracking ChatGPT referral traffic in GA4.
Around those, run a fixed panel of buyer questions on a schedule and log the answers verbatim rather than as a score. Verbatim logs tell you why an answer changed, which a percentage never does. The method is in how to measure LLMO and AI visibility. Treat any single visibility percentage from a vendor tool as a summary of a prompt set you have not seen.
Red flags, starting with guaranteed citations
Say it plainly: nobody can guarantee an AI citation. The output of a generative model varies between runs of the same prompt, no provider sells guaranteed inclusion in a generated answer, and the retrieval and ranking logic sits inside systems no agency has access to. An agency can guarantee its own deliverables, which is a genuinely useful commitment. It cannot guarantee an outcome it does not control, and an offer to do so tells you everything about how the rest of the engagement will be reported.
The second red flag is treating crawler access as sufficient rather than necessary. OpenAI publishes its crawlers and the robots.txt directives that govern them, including OAI-SearchBot, and Anthropic documents ClaudeBot and the robots.txt controls available to site owners. Allowing those user agents is table stakes and takes an afternoon. A proposal whose centrepiece is a robots.txt edit is charging retainer prices for a config change.
Three more worth walking away from. An audit that marks up content the page does not display, which breaches Google's structured data policy outright. A vendor visibility score with no published question set, because the questions determine the number. And an engagement that reports only improvements, because anyone running this honestly for a year has a quarter where the answers got worse. On the commercial questions around scope and price, an AEO agency should be able to break a quote into page count, schema scope, entity cleanup and measurement cadence, and quote those four separately.
Run Answer Engine Optimization With DevCommX
DevCommX ships this as engineering with a named owner on your side: the audit, the page rebuild, the schema, the access fixes and the measurement panel, all on infrastructure you keep. DevCommX benchmarks a well scoped programme with a defined ICP at 40+ qualified demos in ~6 weeks, from our AI SDR work rather than an AEO engagement. If you want to see the change list against your own site before you decide whether to hire an AEO agency at all, look at our AEO work and our GEO services, then book a strategy call.
References
- Google Search Central, Optimizing your website for generative AI features on Google Search, source for the statement that no special optimisations beyond standard SEO practice and crawlable content are required for AI Overviews and AI Mode.
- Google Search Central Blog, Changes to HowTo and FAQ rich results, source for the August 2023 restriction of FAQ rich results to well known, authoritative government and health sites.
- Google Search Central, Search status and updates, Removing the FAQ rich result, source for the retirement of the FAQ rich result in May 2026 and the subsequent removal of the FAQPage documentation.
- Google Search Central, General Structured Data Guidelines, source for the requirement that markup represent the page's main content and not describe hidden content.
- Google Search Central, AI features and your website, source for the nosnippet, data-nosnippet and max-snippet controls that limit what Search displays, including in AI formats.
- Google Search Central Blog, Introducing Search Generative AI performance reports in Search Console, source for first party reporting of impressions inside AI experiences on Search.
- OpenAI, Overview of OpenAI Crawlers, source for OAI-SearchBot and the robots.txt directives that govern OpenAI crawlers.
- Anthropic Help Center, Does Anthropic crawl data from the web, and how can site owners block the crawler, source for ClaudeBot and its robots.txt behaviour.
FAQ
What does an answer engine optimization agency do?
An answer engine optimization agency makes your pages machine extractable. It rewrites headings into the questions buyers ask, places a standalone answer under each one, ships Organization, Product and Article structured data that matches the visible page, reconciles your brand facts across every profile that describes you, and confirms AI crawlers can fetch and render the result.
Is AEO the same as GEO?
No, though they share a foundation. AEO works at the level of a page and a question, optimising for one clean extractable answer. GEO works at the level of a brand and a category, optimising for how a generated response describes and recommends you. Both depend on crawlable, unambiguous, consistent content, so most teams end up buying them together.
Can anyone guarantee a ChatGPT citation?
No. Nobody outside the model providers controls which sources a generated answer cites, the output varies between runs of the same prompt, and no platform sells guaranteed inclusion. An agency can commit to its own deliverables: pages restructured, schema validated, crawler access confirmed, measurement runs completed. Any guaranteed citation offer is either a misunderstanding or a sales tactic.
Does FAQ schema still do anything in 2026?
It no longer earns a rich result. Google restricted FAQ rich results to well known government and health sites in August 2023, then retired the feature entirely from May 2026. FAQPage remains a valid schema.org type that will not harm your site, and a clear question and answer pairing still helps machine parsing, but do not expect a visible search feature from it.
How long does answer engine optimization work take to show results?
Structural and schema changes are usually recrawled within weeks, so the technical half of the work surfaces fastest. Whether that turns into citations depends on how competitive your category is and how strong the incumbent sources are, which takes a quarter or more to read honestly. Measure your page level extractability first, since that is the part you actually control.
Should you hire an AEO agency or train your existing SEO team?
Train your team when they already own technical SEO, can ship structured data, and have capacity to rewrite priority pages. Hire an AEO agency when you need the page rebuild, the schema work and a measurement panel inside one quarter, or when nobody in house has run this before. The skills overlap heavily with technical SEO, so the transfer is realistic.
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