Answer Engine Optimisation

Get cited inside generated answers from ChatGPT, Gemini, Perplexity and Google AI Overviews — measurably.

A growing share of search behaviour no longer ends in a list of links. People ask ChatGPT, Gemini, Perplexity or Google directly, get a generated answer, and act on it. For a business, the question has quietly changed: not just "do we rank?" but "does the answer mention us, and does it get us right?" Answer engine optimisation is the work of being visible inside those answers.

How generated answers cite sources

AI assistants build answers from content they can find, parse and trust. They favour material that is structured, specific and verifiable — clear factual claims, consistent data, pages that answer a question directly rather than dance around it. Sources that are easy to quote get quoted: statistics with clear origins, concise definitions, comparison content that states differences plainly. Vague marketing copy gets skipped.

[S1]Mechanics

How answer engines decide what to cite

  1. Retrieval

    The engine assembles candidate sources from its index and retrieval graph.

    Pages that are crawlable, extractable and topically coherent enter the candidate set. Pages behind heavy scripts or thin on structure never get the chance.

  2. Authority weighting

    Candidates are ranked by how consistently the web identifies and trusts the source.

    Entities, consistent brand references, third-party citations and structured data all contribute to whether a source is treated as quotable.

  3. Extraction and synthesis

    The engine extracts passages it can defend and weaves them into the answer.

    Content shaped as clear, self-contained answers — definitions, steps, comparisons — is disproportionately extractable. Ambiguous prose is skipped.

  4. Citation

    Sources are cited where the answer needs verifiable backing.

    Being cited is a win even without the click: brand presence inside the answer shifts demand and branded search, measurable over time.

AEO, GEO, or just the next shape of SEO

You'll see this called Answer Engine Optimisation, Generative Engine Optimisation, and a handful of other names. The naming matters less than the reality: the fundamentals are an extension of classic SEO, not a replacement for it. Crawlable sites, clean structure, credible content and strong entity signals still underpin everything. What changes is the outcome being measured — presence in generated answers, not just positions on a results page.

[S2]Comparison

Classic SEO vs answer engine optimisation

Classic SEO vs answer engine optimisationClassic SEOAnswer Engine Optimisation
Win conditionPosition one on the results pageCitation inside the generated answer
Content shapePages optimised for keywordsPassages optimised for extraction
Authority basisLinks and domain strengthEntities, consistency and third-party mentions
Click economicsEvery click is measurable revenueAnswers absorb clicks; value shifts to brand and referral
MeasurementRankings and Search ConsolePrompt panels, citation tracking and share of answer

Measuring presence in AI answers

Presence in AI answers is measurable, just differently. The practical approach:

  • Track how assistants answer your buyers' actual questions — category comparisons, "best X for Y", cost and suitability questions — on a regular cadence
  • Record whether your brand is mentioned, how it's described, and which sources the answer drew on
  • Watch citation patterns over time, since the sources being cited tell you what to improve or publish

This becomes part of share of voice reporting, alongside classic search visibility, so the picture stays honest.

[S3]Audit

The citation-readiness audit

Forty-eight checks that determine whether your pages can enter, survive and win in the answer pipeline.

  • Content extractability16
    • answer-shaped passages
    • clear definitions
    • comparative structures
  • Authority signals12
    • third-party mentions
    • consistent entity data
  • Structured data10
    • organisation and person markup
    • FAQ and how-to schema
  • Brand entity strength10
    • knowledge panel presence
    • entity resolution

Why acting now matters

Assistants build their understanding of a category from whatever is available and consistent. Brands that are clearly and accurately described across the web become the default answer; brands that are ambiguous get summarised inaccurately, or not at all. Correcting a mistaken entity profile once an assistant has settled on a narrative is slow, expensive work. The patterns being set now — by what you publish, and by what others publish about you — are the ones that will be expensive to change later.

[S4]Deliverables

What the engagement produces

  • Citation-readiness audit across the 48-point framework
  • Prompt panel baseline across the major engines
  • Content restructure specs for your highest-value pages
  • Entity and structured-data implementation tickets
  • Third-party citation plan: where answers find your category’s sources
  • Monthly share-of-answer reporting against the baseline

What this looks like

Engagements start with a baseline: how the major assistants currently answer your buyers' key questions, what they say about you, and which sources shape those answers. From there, a practical programme — content structured to be citable, entity and source cleanup, and ongoing monitoring of AI answer presence alongside organic share of voice. No promises of guaranteed citations; just systematic work on the inputs that determine whether you're part of the answer.

[Q]Questions

Answer Engine Optimisation: common questions

  • The terms overlap and the industry uses both loosely. AEO usually means being cited inside generated answers; GEO adds the geographic and entity layer. The work is the same either way: make the brand identifiable, trusted and extractable, then measure presence inside answers.

  • No — the changes pull in the same direction. Extractable content is better structured content; entity work is stronger structured data; authority building is authority building. Programmes that treat them as competing budgets usually underfund both.

  • Entity and structured-data changes can show up in weeks. Content restructuring on high-authority pages typically shows in one to three months. The monthly panel shows movement early, before referral or branded-demand effects become visible in analytics.

Tell Me What You Need to Win.

I will tell you honestly whether I am the right person for it.