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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 being invisible to search and AI looks like.

Rankings hold but traffic falls — impressions steady, clicks are not, because the answer is being read on the results page or inside an assistant.
Invisible to AI assistants — ask ChatGPT or Perplexity who does what you do, and competitors are named while you are not.
Content that ranks for nothing — long posts written for a keyword rather than a question, with no extractable answer for an engine to lift.
No line from marketing spend to pipeline — traffic is reported, revenue attribution is not, so the budget is defended with proxies.
Three vendors, three retainers, three contradicting recommendations for what is really one foundation.
A site that reads well to a person and is illegible to a retrieval system — no structured data, comparison facts trapped in styled divs.
Why it persists

Why good sites still fail to get found.

CAUSE 01

Content written for volume, not for questions

Strategy built around keyword volume rather than the questions buyers actually type and speak. High-volume terms attract researchers; buying questions attract buyers, and the two rarely look alike.

CAUSE 02

No structured data, so machines cannot read the claims

Without schema a retrieval system can see what words a page contains but not what it asserts. It has no way to tell a price from a date, or a service from a section heading.

CAUSE 03

A CMS that publishes for humans and nothing else

Clean pages for a browser, illegible to a retrieval system: comparison data rendered as styled divs, answers buried mid-page, and no self-contained passage worth quoting.

CAUSE 04

Measured on traffic instead of pipeline

Traffic is a proxy. When the number that gets reported is sessions rather than qualified pipeline, the work optimises for the proxy and the pipeline does not move.

CAUSE 05

SEO, AEO and GEO treated as three budgets

Three vendors, three retainers and three sets of recommendations that contradict each other. They are one foundation with three outputs, and splitting them pays three times for the same groundwork.

Delivery framework

How Corelynx builds a growth stack, 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

            What you get from a growth stack engagement.

            Technical auditCommercially prioritised findings, not an undifferentiated warning list.
            Structured data implementationAcross every template, so machines can read what each page asserts.
            Content architectureThe question map, the hub-and-spoke plan, and the internal link matrix.
            AI visibility baselineWhat ChatGPT, Perplexity, Claude and Google AI Overviews currently say about you.
            llms.txt and crawler accessibilityExplicit access for the assistants whose citations you want.
            Core Web Vitals remediationMeasured against field data, not lab scores.
            Attribution wiringFirst touch through to the CRM record, so spend answers to pipeline.
            Monthly assistant-visibility reportingThe same buyer questions asked on a schedule, with what changed.
            Pricing transparency

            Engagement tiers & published pricing

            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.

            Engagement tiers & published pricing
            Offering Investment Model What it covers
            Where you actually standVisibility Diagnostic $7,500–$12,000 See where yours lands 2–3 weeks, fixed fee Technical audit, AI visibility baseline across ChatGPT, Perplexity, Claude and Google AI Overviews, content gap analysis, and a prioritised roadmap you own outright.
            Fix the floorFoundation Build $18,000–$45,000 See where yours lands 6–12 weeks, milestone-billed Technical remediation, structured data across every template, content architecture with the question map and internal link matrix, and attribution wired through to the CRM record.
            Compound itOngoing Growth $4,500–$12,000/mo See where yours lands Monthly retainer, 3-month minimum Content production against the question map, technical maintenance, monthly assistant-visibility tracking, and reporting measured against pipeline rather than sessions.
            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.

            How do SEO, AEO and GEO fit together?

            They get sold as three services because three retainers bill better than one. The groundwork is largely shared: a page a search engine can crawl, parse and rank is most of the way to a page an answer engine can quote, and both depend on the same structured data and the same clarity about what the page actually asserts.

            Where they genuinely differ is the unit that wins. Classic SEO competes at the page level for a ranked position. Answer-engine optimisation competes at the passage level — a self-contained block that can be lifted whole and still make sense. Generative-engine optimisation competes at the entity level, on whether the wider web corroborates who you are consistently enough for a model to state it confidently.

            Buying them separately pays three times for the shared foundation and produces three sets of recommendations that contradict each other on the specifics.

            Technical foundationRendering, speed, crawler access, structured data, clean information architecture. Serves all three outputs and is the prerequisite for every one of them.
            SEO — the pageCompetes for a ranked position on a query. Depends on relevance, authority and the technical floor being sound.
            AEO — the passageCompetes to be the block an assistant quotes. Depends on self-contained answers, comparison tables, and answering the question in the first sixty words.
            GEO — the entityCompetes on whether the web agrees about who you are. Depends on consistent descriptions across every profile, directory and mention that already exists.

            What a citable page actually looks like

            There is a measurable shape to the passages assistants quote, and most B2B pages miss it in the same two ways. The answer arrives too late — after four paragraphs of context-setting that a human skims and a model discards — and the passage is not self-contained, so lifting it out of the page leaves it meaningless.

            The fix is structural rather than stylistic. Answer the question the page is named after in the first sixty words. Make each answer block long enough to stand alone but short enough to quote whole; passages in the 134-to-167-word band get cited noticeably more often than shorter or longer ones. Put comparative information in a real table, because engines parse tables as structured data and cite them far more readily than the same facts written as prose.

            None of that makes a page worse to read. A page that opens with its conclusion serves the impatient human and the extraction model equally well, which is why we have never had to trade one against the other.

            How to evaluate anyone selling AI-search visibility

            • Ask what they will do off your website. If the whole plan is on-site content, they are selling SEO with new vocabulary — entity consistency is off-site work by definition.
            • Ask how they will measure it, specifically. "Assistant mentions" is not a metric unless they name how the query set is built and how often it is run.
            • Ask what they would do first. Content volume as the opening move, before the technical floor and the footprint are dealt with, predicts a year of work that never compounds.
            • Ask whether they will fix your directory and profile listings. It is unglamorous, hard to bill as a recurring retainer, and among the highest-leverage work available.
            • Ask what happens if AI search does not send you traffic. An honest answer accepts that the effect surfaces first as branded search and direct visits, not as a referral line in analytics.
            Outcome model

            What changes when buyers can actually find you.

            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

            Frequently asked

            SEO, AEO and GEO questions, answered straight.

            SEO competes for a ranked position on a results page. AEO — answer engine optimisation — competes at the passage level, to be the specific block an assistant quotes when someone asks a question. GEO — generative engine optimisation — competes at the entity level, on whether the wider web describes you consistently enough for a model to state what you do with confidence. They share most of their groundwork: a page a search engine can crawl and parse is most of the way to a page an answer engine can quote. Buying them as three separate retainers pays three times for that shared foundation.

            Technical fixes register within weeks — crawlability, speed and structured data changes are picked up on the next crawl. Content and entity work compounds over quarters rather than months. The honest framing is that the first ninety days buys you a foundation and a baseline, not a traffic curve, and any agency promising a revenue change inside one quarter is describing paid media rather than organic visibility.

            Four ways, and none of them is a referral line in analytics. Track branded search volume, because assistant mentions produce searches for your name. Query the assistants directly on a schedule — the same buyer questions asked monthly, recording whether you appear and what is said. Watch impressions and average position in Search Console independently of clicks, since rising impressions against flat clicks is evidence of answer-surface visibility rather than failure. And instrument the first conversation: ask every new enquiry how they found you and store it as a field, not as anecdote.

            That is a business decision with a real trade-off, not a security default. GPTBot and ClaudeBot are used for both training and live retrieval, so blocking them also removes you from the answers those assistants generate. If your strategy depends on being cited when a buyer asks an assistant for recommendations, blocking is self-defeating. If your content is genuinely proprietary and citation is not the goal, blocking is reasonable. We implement whichever you choose and document the consequence either way.

            A visibility diagnostic runs $7,500 to $12,000 as a fixed fee over two to three weeks and produces a scored assessment plus a prioritised roadmap you own outright. A foundation build runs $18,000 to $45,000 over six to twelve weeks. Ongoing growth retainers run $4,500 to $12,000 a month with a three-month minimum. The diagnostic is deliberately standalone — roughly half of diagnostic clients do the remediation themselves or with an existing agency, and the report is written so that is possible.

            See where yours lands

            Yes, and it is a common arrangement. The split that works best is Corelynx owning the technical foundation, structured data and measurement while the incumbent agency owns content production and campaigns, because those are genuinely different skills and the friction usually comes from one team being asked to do both. What does not work is two parties both owning the technical layer — the recommendations conflict and neither is accountable for the result.

            The foundation overlaps heavily and anyone claiming otherwise is selling novelty. What genuinely differs is the unit of competition and where the work happens. Classic SEO optimises pages for rankings. Answer engines quote self-contained passages, which changes how a page should be structured — the answer belongs in the first sixty words, not the conclusion. And entity consistency is off-site work by definition: making the twenty places that already describe your company agree with each other. If a proposal is entirely on-site content, it is SEO with new vocabulary.

            The likely path is that rankings hold while traffic declines, because more answers are being read on the results page or inside an assistant without anyone visiting the source. The compounding risk is the consideration set: when a buyer asks an assistant who does what you do and competitors are named while you are not, you are excluded before an evaluation begins. That exclusion is not visible in your analytics, which is what makes it easy to defer and expensive to have deferred.

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