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Answer Engine Optimization

AI Overviews and Copilot answer a growing share of commercial queries above the organic results. The citation inside that answer now does the work the blue link used to.

Request an auditHow it is measured

At a glance

Pillar
AI Visibility
Cycle time
Weeks
Prerequisite
Pages that rank
Measured on
Citation share
Overlap with SEO
Substantial

Answer engine optimisation is the practice of structuring content so that zero-click answer layers on search engines lift and attribute it as a source.

Answer Engine Optimization · definition

Why the summary took the click

When the generated summary satisfies the question, the page that would have earned the visit is never opened. Presence inside the summary is the only remaining exposure.

The answer sits above the click

The summary resolves the query. Being one of its sources is the whole opportunity.

Extractability beats comprehensiveness

Answer engines lift passages, tables and defined facts. Narrative pages that bury the claim in paragraph six are structurally hard to quote.

The same work lifts classic search

Schema, claim-first passages and comparison tables improve featured snippets and People Also Ask at the same time.

How it works

  1. Map the triggering queries

    Which of your priority queries produce a generated answer at all, and which currently cite a competitor.

  2. Restructure for the lift

    Definitions near the top, claims as standalone sentences, comparisons as real tables rather than prose.

  3. Deploy type-appropriate schema

    FAQPage, Article, Product and Organization where they match the page, not generic markup everywhere.

  4. Publish crawler policy

    llms.txt and access decisions made per content type rather than by default.

  5. Track passage-level citation

    Which specific passage is being lifted, and whether it says what you intended.

What is included

01

Trigger and citation baseline

Which priority queries generate answers, and who is cited today.

02

Passage rewrites

Priority pages restructured for extraction without losing their ranking.

03

Schema deployment

Validated, type-appropriate structured data across page types.

04

Comparison structures

Tables and matrices built to be lifted whole.

05

Crawler access policy

Per-content-type decisions, documented.

06

Monthly review

Citation share, snippet retention and passage-level detail.

How it is measured

Citation share inside AI Overviews and Copilot answers for the queries that carry commercial intent, tracked on a fixed query set.

  • AI Overview trigger rate: which of your priority queries produce a generated answer at all
  • Citation share: how often you are one of the sources shown for those answers
  • Passage match: which specific passage of yours is being lifted, and whether it says what you want
  • Snippet retention: whether existing featured snippets survive the rewrite work
  • Query coverage: how much of the priority query set you appear on at all

Baseline figures · to supply per client

AEO and GEO are not the same thing

Answer engine optimisation compared with generative engine optimisation
DimensionGEORankingBite
Primary surfaceStandalone assistantsZero-click layers on search engines
TriggerA conversational promptA query that produces a generated answer
Dominant leverEntity resolution and corroborationPage structure, schema and extractable passages
Content unitThe brand as an optionThe passage as a quotable fact
Overlap with SEOPartialSubstantial: the same pages compete in both

When AEO is the right call

A good fit when

  • Your category queries already return AI Overviews.
  • You have a body of ranking pages that are not being cited.
  • You can ship structural rewrites and schema across priority pages.

Not the right service when

  • Your priority queries rarely trigger generated answers.
  • The site has unresolved crawl or render problems.
  • You rely on gated content; there is nothing extractable to quote.

Most engagements run AEO and GEO together, because the underlying pages and the measurement infrastructure are shared.

Frequently asked questions

Does optimising for AI Overviews cost us organic clicks?

Not usually. Pages restructured for extraction tend to hold or improve their ranking, and appearing as a cited source recovers some of the visibility lost to the summary. Doing nothing is the option that reliably loses clicks.

What is llms.txt and do we need one?

It is an emerging convention for telling AI crawlers which content matters. It is cheap to deploy and we include it, but it is hygiene rather than a lever: structure and sourcing do the real work.

Should we block AI crawlers?

A genuine trade-off, decided per content type. We usually recommend open access for editorial and reference content, closed for original research with a public summary.

How quickly do AI Overviews respond to changes?

Structural rewrites and schema typically register within weeks on pages that already rank. Queries where you do not rank at all take longer, because ranking is still the entry condition.

Related services

See which answers you are missing from.

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