AI SEO

AI SEO makes your catalogue readable, retrievable and quotable

Classic SEO optimised for a ranked list of ten links. AI SEO optimises for systems that read, compress and re-express your content as an answer. That changes what you publish, how you structure it, and how visibility is measured.

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Optimisation target: Answers, not just rankings
Primary unit: Entities & claims
Surfaces covered: AI + classic search

AI visibility monitorIllustrative

ChatGPTCited
Google AI answersCited
PerplexityMentioned
GeminiNot surfaced

Answer inclusion rate

38%of tracked prompts

Cited source share

21%of citations

Entity confidence

72/100

Brand, product and category clarity

Classic + AI overlap

46%

Queries visible on both surface types

Search behaviour

People stopped asking for pages. They started asking for conclusions

A shopper who once searched “best running shoes for flat feet” now describes their situation in a sentence and expects a short, decided answer. The intermediate step — scanning results — is being absorbed by the model.

Queries are longer, conversational and full of constraints.
Follow-up questions replace second and third searches.
The answer arrives before any brand has been chosen by the user.
Being unquoted is functionally the same as being invisible.

Classic search

Ten links, user decides

01Keyword typed
02Ranked list returned
03User scans titles and snippets
04User clicks two or three results
05User forms their own conclusion

Position on the page is the main visibility currency.

AI search

One answer, model decides

01Situation described in full sentences
02Query decomposed into sub-questions
03Sources retrieved and compared
04Answer synthesised with citations
05User asks a follow-up

Being retrievable and quotable is the visibility currency.

What AI SEO actually is

Three jobs, done in order

AI SEO is not a tactic layer bolted onto existing SEO. It is a sequence: be understood, be retrievable, be worth quoting. Skipping the first two makes the third impossible.

Machine comprehension

Entities, attributes and relationships stated explicitly — brand, products, categories, materials, use cases, compatibility — so a model can describe your catalogue without guessing.

Retrievability

Clean crawl paths, fast server responses, rendered HTML content and consistent canonical structure so passages can be fetched and indexed.

Structured data

Schema that matches on-page reality: Product, Offer, Breadcrumb, FAQ and Organisation markup used as confirmation, not decoration.

Quotable content

Self-contained passages that answer one question with a direct claim, the reasoning behind it and the constraint it applies under.

Corroboration

Consistent facts across your own site and the third-party sources models already trust, so nothing contradicts and confidence rises.

How answers get built

Your content passes five gates before it is quoted

Each gate discards candidates. Most ecommerce content fails at retrieval or extraction long before quality is ever assessed.

Failing early is silent — there is no ranking report for it.
Every gate maps to a fixable technical or editorial cause.

Retrieval to answer pipelineSequenced

01
Crawl
Can the surface reach the URL, quickly and without blocks?
02
Parse
Is the substance in the HTML rather than behind interaction?
03
Extract
Can a single passage stand alone as an answer to one question?
04
Compare
Does it agree with other sources on the same fact?
05
Cite
Is it the clearest available statement to attribute?

Our AI SEO system

Five inputs feed one outcome: your brand being the source the model reaches for

AI SEO input modelIllustrative

Entity definition
Structured data
Answer-shaped content
Technical retrievability
External corroboration

Cited in generated answers

82/100

Composite of technical, product, category and AI-search signals.

Signal audit

What we measure before writing a single page

Illustrative diagnostic output. Every row is a signal a model uses when deciding whether your content can be trusted as a source.

AI readiness diagnosticIllustrative

AI readiness score

64/100

Entity clarityPartial
Product schema validityStrong
Rendered content coverageGaps
Passage self-containmentWeak
Fact consistency across sourcesGood
Category answer coverageGrowing

Content model

Write for extraction, not for word count

A page that reads well but cannot be sliced into a quotable claim contributes nothing to an answer. We restructure existing content before adding more.

Passage rewrite pattern

Illustrative rewrite pattern used across category and product templates.
Content element	Common form	Extraction-ready form
Category intro	Brand story paragraph	Direct definition + who it suits
Product benefit	Adjective list	Claim + measurable reason
Comparison	Feature table only	Stated verdict per use case
Buying guidance	Long scrolling guide	One question per heading
Specifications	Image of a spec sheet	Text specs mirrored in schema

Where AI SEO sits

It does not replace ecommerce SEO — it depends on it

Retrievability, indexation and site architecture are shared foundations. AI SEO adds the interpretation layer on top of work that must already be sound.

Ecommerce SEOthe commercial search foundation AI SEO builds on.
AEOanswer engine optimisation for direct question intent.
GEOgenerative engine optimisation for synthesised responses.

L01Technical foundationCrawl, render, speed, indexation control

L02Commercial architectureCategory, product and facet structure

L03Semantic layerEntities, attributes, structured data

L04Answer layerQuotable passages and question coverage

L05Corroboration layerExternal consistency and citations

Surface coverage

One system, several answer surfaces

Surfaces differ in how they retrieve and how they cite, but they reward the same underlying clarity.

Input to surface mapIllustrative

Entity graph
Structured data
Answer content
External signals

ChatGPT
Google AI answers
Perplexity
Gemini
Copilot

Discovery outcomes

Brand mentioned
Source cited
Product recommended

Measurement

What we track for AI SEO

Illustrative demo data showing the measurement model, not client results. Reporting pairs AI answer inclusion with the classic search metrics you already trust.

Illustrative demo data

Answer inclusion rate38%Share of monitored prompts where the brand appears
Citation share21%Share of citations attributed to owned pages
Entity confidence72Composite clarity score across brand and catalogue
Assisted non-brand sessions+29%Sessions from AI referrers and answer-driven discovery

Figures shown are illustrative interface data, not client results.

FAQ

AI SEO questions

It shares the technical foundation — crawlability, rendering, indexation and site architecture — but changes the optimisation target. Traditional SEO optimises for position in a ranked list. AI SEO optimises for being retrieved, understood and quoted inside a generated answer, which puts far more weight on entity clarity, structured data and self-contained passages.

Yes. AI systems retrieve from indexed content, so classic indexation and architecture work is a prerequisite rather than an alternative. In practice the two programmes share roughly the same technical base and diverge at the content and measurement layer.

Through prompt-level monitoring rather than keyword positions alone: how often the brand appears in answers for a tracked prompt set, how often owned pages are cited as sources, how consistently entities are described, and how AI-referred sessions and assisted conversions trend alongside classic organic performance.

Technical retrievability and structured data fixes can change how quickly content is re-read within weeks. Answer inclusion usually moves later, because it depends on new quotable content being crawled, corroborated and then selected. Treat the first quarter as foundation work and expect inclusion trends to become readable after that.

Large catalogues benefit most, because the work is template-level. Fixing how one category or product template states entities, specifications and buying guidance propagates across thousands of URLs at once.

An AI readiness diagnostic, entity and structured data definition, technical retrievability fixes, template-level content restructuring for extraction, question coverage across the catalogue, external consistency work, and prompt-level visibility reporting.

Start with a diagnostic

See how AI search currently describes your brand

We map the prompts that matter in your category, show what answer surfaces currently say, and identify the specific gaps blocking your catalogue from being cited.

Book a Strategy Call

No obligation. A senior strategist reviews your store before the call.