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Growth Stack

Growth Stack: SEO, AEO, GEO & Digital Presence

Being findable stopped meaning ten blue links. We build the technical foundation, structured answers and measurement that get you surfaced by search engines and cited by AI assistants — then connect it to the CRM so you can prove it worked.

REVENUE VISIBILITYCRM ADOPTIONMANUAL WORKFLOWSREPORTING TRUSTSTALLED CHANGEIMPL. RISKSYMPTOMS INCORELYNXDIAGNOSTIC ROUTERCUSTOM APPS & MVPCRM SERVICESAI TRANSFORMATIONSALESFORCEFRACTIONAL CTO5 CLEAR TRACKSDIAGNOSE→ ASSESS→ ROADMAP→ BUILD→ OPERATE
Direct answer · What are SEO, AEO, GEO and AIO, and which does my business need?

SEO gets you ranked in a list of links. AEO (Answer Engine Optimisation) gets you quoted in the answer box above that list. GEO (Generative Engine Optimisation) gets you cited inside ChatGPT, Perplexity, Google AI Overviews and Copilot. AIO is the umbrella term for optimising across all AI-mediated discovery. You need all of them, because they share one foundation — crawlable technical structure, genuinely useful answers to specific questions, and machine-readable markup — and diverge only in the last mile. The mistake is treating them as four separate budgets rather than one operating system with four outputs.

Executive summary

Your buyers are no longer starting at a list of links. They ask an assistant, read the synthesised answer, and click through to one or two sources it named. If you are not one of those sources, you are not in the consideration set — no matter where you rank. We build the technical foundation, the structured answers and the measurement that put you inside those responses, and we wire it to the CRM so you can see which of it actually produced pipeline.

58.5%
Of US Google searches ended without a click in 2024 — the answer never left the results page
15% → 8%
Click-through to a result, with and without an AI summary present (Pew, July 2025)
1%
Of visits where anyone clicked a source cited inside the AI summary itself
~25%
Forecast fall in traditional search volume by 2026 as buyers move to AI assistants (Gartner)
Sources: SparkToro/Datos US clickstream study, 2024 (58.5%); Pew Research Center, 22 July 2025, n=900 US adults (15% vs 8% click-through); Bain & Company Consumer Health Survey, 2024 (80% zero-click reliance); Gartner press release, 19 February 2024 (25% forecast decline). Every figure is from a primary source and dated.
Who this is for
  • Companies whose organic traffic is falling while impressions hold steady
  • Teams who rank well but are absent when a buyer asks an AI assistant
  • Marketing leaders who cannot show which activity produced last quarter's pipeline
  • Anyone about to rebrand or replatform, before the structure gets locked in
When to act — trigger conditions
  • Traffic is dropping and rankings have not moved
  • A prospect says they asked ChatGPT about vendors and you were not mentioned
  • Marketing reports sessions; the board asks about pipeline
  • Before a replatform, while the technical decisions are still reversible
Operational symptoms

What this problem looks like from the inside.

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Why it persists

The structural causes underneath the symptoms.

CAUSE 01

CAUSE 02

CAUSE 03

CAUSE 04

CAUSE 05

Delivery framework

How Corelynx runs this work, phase by phase.

Diagnose what a machine actually sees

We crawl the site the way a search engine and a retrieval system do — render-blocking scripts, orphaned pages, thin or duplicated content, missing and malformed structured data, sitemap versus navigation disagreements, Core Web Vitals against field data rather than lab scores. You get a prioritised list with the commercial cost of each item, not a 200-row spreadsheet of undifferentiated warnings.

    Rebuild the foundation

    Server-rendered HTML so content exists before JavaScript runs. Schema.org markup — Organization, Service, FAQPage, BlogPosting, BreadcrumbList — so a machine can parse what each page asserts rather than guessing from prose. Clean canonical structure, real redirects for legacy URLs, an llms.txt feed for AI crawlers. This is the layer everything else compounds on, and it is the layer most agencies skip because it is invisible in a screenshot.

      Write answers, not articles

      One question per URL, answered in the first forty words, then substantiated. Attributed figures with a named source and a year, because an answer engine that cannot verify a claim will not repeat it. This is the single biggest difference between content that ranks and content that gets quoted — and it is why our own Solution Desk is built the same way.

        Optimise for the answer, not the link

        AEO and GEO work is concrete: structure passages so they can be lifted intact, cover the entity relationships an assistant needs to place you in a category, earn mentions on the sources those models were trained on and retrieve from. Then track whether you are actually being cited — by asking the assistants directly, on a schedule, and recording what they say.

          Close the loop to revenue

          Traffic is a proxy. We wire form capture, chat and assessment tools into the CRM so a lead carries its source, the page it converted on and the question that produced it. Marketing spend then argues from pipeline rather than sessions — which is the only version of this conversation a CFO finds persuasive.

            What you receive

            Explicit deliverables. No mystery boxes.

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            Pricing transparency

            Fixed-scope diagnostics. You keep the findings whether or not you continue with us — a report you cannot act on without the author is a subscription, not a deliverable.

            OfferingInvestmentModelWhat it covers
            $7,500 – $12,000Visibility Diagnostic
            Technical audit, AI visibility baseline, content gap analysis, prioritised roadmap. Two to three weeks. See where yours lands
            $18,000 – $45,000Foundation Build
            Technical remediation, structured data, content architecture, attribution wiring. Six to twelve weeks. See where yours lands
            $4,500 – $12,000/moOngoing Growth
            Content production, technical maintenance, AI visibility tracking, monthly reporting against pipeline. See where yours lands
            How these fit the Corelynx engagement model

            What actually makes a page citable

            Assistants quote passages, not pages. The unit that gets cited is a paragraph that answers a specific question completely, without needing the surrounding article for context. A page organised as a narrative — building an argument over eight hundred words before the payoff — is excellent for a human reader and nearly useless as a citation source.

            This does not mean writing for machines. It means front-loading: state the answer, then explain it. A page that opens with its conclusion serves the impatient human and the extraction model equally well, and there is no page we have written where doing this made it worse to read.

            The consistency problem nobody budgets for

            Assistants weight information that agrees with itself across independent sources. If your site says one thing, your LinkedIn profile says another, and three directory listings each carry a different service description, none of it is confidently citable — the model has no basis for choosing between them.

            This is why the highest-leverage GEO work is often not on your website at all. It is making the twenty places that already describe your company agree with each other: directory profiles, review sites, partner pages, social bios, old press mentions. Unglamorous work, rarely proposed by agencies because it is hard to bill as a recurring retainer, and consistently effective.

            How to measure work that produces no clicks

            This is the reporting problem that causes good programmes to be cancelled. If a buyer asks an assistant for recommendations, reads a summary that includes you, and then searches your name directly, your analytics records a branded direct visit. The work that created the demand is invisible to the tool measuring it.

            • Track branded search volume as a primary metric. Assistant mentions produce searches for your name, and that is where the effect surfaces first.
            • Query the assistants directly, on a schedule. Ask ChatGPT, Claude, Perplexity and Google's AI surfaces the questions your buyers ask, monthly, and record whether you appear and what is said about you.
            • Watch impressions and average position in Search Console independently of clicks. Rising impressions against flat clicks is evidence of answer-surface visibility, not failure.
            • Instrument the first conversation. Ask every new enquiry how they found you and store it as a field, not as anecdote.
            • Accept a longer feedback loop. This compounds across quarters; judged month to month it will always look like it is not working.

            What we would do in the first ninety days

            Fix the technical floor first — rendering, speed, structured data, crawler access — because nothing downstream compensates for a page an engine cannot read or will not wait for. Then rebuild the pages that answer real buying questions so each leads with its answer rather than arriving at one. Then reconcile the off-site footprint so the web agrees about who you are and what you do.

            Only after those three is content volume worth funding. Publishing into a site with an unresolved technical floor and an inconsistent footprint is the most reliable way to spend a year producing work that never compounds.

            Outcome model

            What changes when this works.

            OUTCOME 01

            Findable by search engines and quotable by answer engines, from one foundation rather than three budgets

            OUTCOME 02

            Content that answers a specific question well enough to be extracted

            OUTCOME 03

            A defensible line from marketing activity to qualified pipeline

            OUTCOME 04

            A technical base that does not have to be rebuilt at the next replatform

            Keep exploring

            Related practices

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            Bring your assessment result. The first conversation is about context and fit — nothing more.

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            Tell us the situation; we'll outline how we'd sequence the diagnostic and what it would examine. Or see the engagement model first.

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