SEO & Answer-Engine Optimisation

About SEO & Answer-Engine Optimisation

SEO and Answer-Engine Optimisation is Metacubic's line for being found in both places that now matter: ordinary search results, and the answers assistants give when somebody asks about your category.

Metacubic's own framing is that classic SEO targets ranking in Google's blue links while AEO targets being the cited answer inside AI tools, and that the technical foundations overlap. The company also uses AEO and GEO as names for the same discipline.

The overlap is the useful part of that claim, and it is worth understanding precisely, because the market around this acronym contains a lot of confident nonsense.

What does the SEO and AEO line cover?

Metacubic lists six areas: technical and on-page SEO covering site architecture, Core Web Vitals, structured data and content; answer-engine optimisation aimed at citation by ChatGPT, Perplexity and AI Overviews; content and schema; analytics and tracking with event tracking, dashboards and attribution; conversion-focused work; and structured CRO experiments.

The stated deliverables are a prioritised SEO and AEO action plan, on-page technical and schema improvements actually shipped rather than recommended, event tracking and a reporting dashboard, and a content roadmap mapped to buyer intent.

The published process runs audit, fix and optimise, create and convert, then measure and iterate.

Does schema markup get you into AI Overviews?

This deserves a precise answer rather than a sales one.

Google's own documentation states there is no special markup or schema that makes content eligible for AI Overviews or AI Mode, that these features draw from the same index as ordinary search, and that a page must be indexed and eligible to show a snippet before it can appear at all. Google is explicit that standard SEO best practice is the requirement, not a separate discipline.

So schema markup is genuinely worth doing, because it earns rich results in classic search and makes your content machine-readable. But nobody should be sold schema as the switch that turns on AI citations. It is not.

What does change in practice is structure. AI answers tend to quote a heading and the passage beneath it, so pages written as a series of self-contained answers get quoted more often than pages written as one continuous argument. That is an editorial decision, and it costs nothing.

Why does the same work not apply to every AI assistant?

Because different systems work differently, and Google's guidance only describes Google.

AI Overviews and AI Mode are built on Google's index and ranking systems, so strong organic performance is the foundation there. ChatGPT, Perplexity and other assistants use their own retrieval and their own source selection, and do not follow Google's ranking signals.

The practical consequence is that a single tactic aimed at all of them at once is usually a tactic aimed at none of them. The things that help across the board are unremarkable: content that is genuinely useful, accessible to crawlers, clearly structured, and factually reliable enough to be worth citing.

Anyone promising a specific mechanism for getting cited by a named assistant is describing something that neither Google nor OpenAI publishes.

How is success measured?

Metacubic's stated measurement approach is event tracking and dashboards covering traffic, rankings, AI citations, leads and conversion rate, tied back to revenue where that is possible.

The honest difficulty is that AI citation measurement is immature. Referrals from assistants are harder to attribute than search clicks, and a citation that a reader acts on without clicking leaves no trace in your analytics at all.

That is a reason to keep watching conventional metrics rather than replacing them. Leads and revenue still work as measures whatever channel produced them, and they are considerably harder to game than a visibility score.

Who implements the recommendations?

Since Metacubic is a development studio as well, the company states it designs, builds and instruments landing pages rather than only recommending changes.

That matters more than it sounds. A large share of SEO recommendations die because somebody has to implement them and nobody does. Audits that end in a document tend to stay documents.

It also means technical fixes touching site architecture, page speed or rendering can actually be carried out rather than passed to a separate developer who was not in the conversation.

Who should choose something else?

If you have no product or no clear offer yet, this is premature. Traffic makes a weak offer fail faster and more publicly.

If your site is slow, broken or impossible to update, Metacubic Web comes first. Optimising pages that will not load is wasted money.

If you already have enough traffic and the problem is that visitors leave without enquiring, Conversion Funnel Design is the line that addresses that directly.

And if what you want is guaranteed rankings, a fixed timeline for position one, or any promise about a specific AI assistant citing you, no honest supplier can offer it. Anybody who does is either guessing or planning to do something that will eventually cost you the rankings you have.