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(build 03)sample build

A sample build: how we would connect existing content to what buyers search for on Google and ask AI assistants. It is an illustration of our approach for a typical business, not a client case study.

the problem
Content existed, but there was no single strategy connecting it to what buyers search for or ask AI assistants.
built for
A stronger foundation for traditional search and for being found in AI answers.

(01)the system

how it runs, step by step.

The system for Search and AI visibility engine
  1. 01Search intent
  2. 02Topic clusters
  3. 03SEO content
  4. 04AEO content
  5. 05GEO / entity content
  6. 06Structured data
  7. 07AI search monitoring
  1. 01

    Search intent

    We map the questions buyers ask at each stage, using Google Search Console, Ahrefs or Semrush, People Also Ask and sales call notes.

  2. 02

    Topic clusters

    Questions are grouped into clusters, each with a pillar page and supporting pages, so the site covers a subject fully instead of in scattered posts.

  3. 03

    SEO content

    Pages are written or rewritten for the search intent behind each cluster, with clear headings, internal links and a reason to rank.

  4. 04

    AEO content

    Direct answers and FAQ sections are written so search features and assistants can lift a clear, accurate reply from the page.

  5. 05

    GEO / entity content

    We make the business easy for AI models to understand: consistent facts about who you are and what you do, on your site and on the profiles models read.

  6. 06

    Structured data

    Organization, Service, FAQPage and Article schema in JSON-LD, plus an llms.txt file, so machines read the pages the way people do.

  7. 07

    AI search monitoring

    A regular check of how ChatGPT, Perplexity, Gemini and Google AI Overviews answer your key questions, and whether they mention or cite you.

(02)what we would measure

how we would know it works.

Consider this build if you publish content but cannot say which buyer question each piece answers. It suits businesses that want to be found both in search results and in the answers AI assistants give.
  • Non-brand organic clicks
  • Share of target questions where the brand is cited in AI answers
  • Pages ranking per topic cluster
  • Organic leads

(03)services it uses

hire any piece on its own.

solutionfound on Google and in AI answerslevel 3the full growth system
book a growth audit

(04)more builds

other sample builds.

  1. sample build 01

    AI lead qualification and sales automation

    problemInbound leads were being handled manually across several channels, and response times depended on who was free.Meta / Google AdsLanding pageAI lead qualificationWhatsAppCRMSales teambuilt forFaster responses, automated qualification, less manual work and the same follow-up for every lead.open the build
  2. sample build 02

    Automated business intelligence

    problemBusiness data was spread across ad platforms, the CRM, the website and sales sheets, and reports were assembled by hand.Google + Meta + CRM + Website + SalesData pipelineUnified dataBI dashboardAutomated reportingbuilt forOne source of truth, faster reporting and decisions made from the same numbers.open the build

Sample builds show how we would approach a problem. They are not client case studies and make no claims about results.

(05)questions

this build, answered.

A topic cluster is a pillar page on one subject with supporting pages that each answer a narrower question, all linked together. It shows search engines and AI models that your site covers a subject in depth, which makes your pages easier to rank and to cite. Clusters are built from real buyer questions found in Search Console, Ahrefs or Semrush and sales calls.

An llms.txt file is a plain text summary at the root of your site that tells AI models what the business does and which pages matter most. It is a small, low-cost addition rather than a ranking factor on its own. We add it alongside Organization, Service, FAQPage and Article schema so machines get the same clear facts that people do.

The groundwork typically takes a few weeks, and the content then builds month by month. The first weeks cover intent research, topic clusters, structured data and a baseline check of how ChatGPT, Perplexity, Gemini and Google AI Overviews answer your key questions. Search and AI visibility build over months, so we track progress against that baseline rather than promising rankings.

(06)your move

want this built in your tools?

Tell us where the bottleneck is. We'll show you what we would automate, build or optimise first.

growth audit · 30 min · google meet · with the founders

  1. 01

    the bottleneck

    Where time, money or customers are leaking, in your tools and numbers.

  2. 02

    the first build

    What we would automate, build or optimise first, and why that one.

  3. 03

    what it takes

    Scope, timeline and a fixed price. If we are not the right fit, we say so.

book a growth audit

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