Hub · Practice 01

AI SEO Consulting Services

Generative Engine Optimisation (GEO) and Answer Engine Optimisation (AEO): getting your brand cited, recommended, and extracted inside ChatGPT, Gemini, Perplexity, and Google AI Overviews.

Direct Senior Consultant

Direct access to an 8+ year enterprise SEO veteran. No account managers or junior teams.

Enterprise & ASX Track Record

Proven multi-million-traffic growth across enterprise banking, retail, insurance and FMCG search programs.

Engineered for Results

Data-led diagnostics, clear engineering deliverables, and zero lock-in contracts.

[SEO] Practice 02
Looking for Enterprise Technical SEO & Site Migrations?

Explore our core organic search practice for crawl architecture, migrations, and executive retainers.

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[01]Overview

The Shift from Search Links to Answer Engines

Search is undergoing its biggest structural transformation in 25 years. Buyers no longer just scroll through ten blue links: they ask ChatGPT, Gemini, Perplexity, and Google AI Overviews complex, multi-layered questions, and they act on the synthesised recommendations.

For Australian enterprise brands, success is no longer just ranking on page one: it is being recognised as an authoritative entity and cited directly inside the answer.

Traditional Search (SEO)

Optimises for the Click

Targets keyword rankings on SERPs to earn organic visits. Measures success through impressions, position, and click-through rates.

AI Search & GEO

Optimises for the Citation

Targets inclusion in LLM-generated answers. Measures success through citation frequency, entity clarity, and recommendation share of voice.

Read the technical AI information fact sheet

[02]Specialised Services

Four Deep-Dive AI Search Services

Every service is engineered as a standalone engagement or a foundational component of your broader organic search strategy.

AUDOrganisations needing a clear diagnostic baseline of current AI visibility

Agentic AI Technical Audit

A measurement of your current presence in AI answers, the sources those answers draw from, and the gaps competitors are filling instead.

Key Focus Areas:
  • LLM Search Perception & Query Coverage Analysis
  • AI Bot Access Audit (GPTBot, ClaudeBot, Google-Extended)
  • llms.txt Architecture & Machine-Readable Content Gaps
AEOBrands wanting to be directly quoted in conversational search

Answer Engine Optimisation

Get cited inside generated answers from ChatGPT, Gemini, Perplexity and Google AI Overviews: measurably.

Key Focus Areas:
  • Extractable Answer & Modular Content Structuring
  • Dense Schema.org & Semantic Entity Mapping
  • Perplexity, Copilot & AI Overviews Direct Sourcing
UCPeCommerce & Service businesses targeting AI assistant recommendations

AI Assistant & UCP Optimisation

Become the brand AI assistants recommend when buyers ask: through entity clarity, credibility and monitoring.

Key Focus Areas:
  • Universal Commerce Protocol (UCP) & Agent Readiness
  • Brand Entity Disambiguation Across Third-Party Data Sources
  • Continuous Prompt Evaluation & Recommendation Monitoring
[03]Methodology

How We Scale Your AI Search Visibility

A proven 4-stage framework to take your enterprise from unseen in LLMs to the authoritative, cited market leader.

  1. Diagnostic AI Audit & Citation Baseline

    Week 1–2

    Discover where LLMs find you, and where competitors are cited instead.

    We run exhaustive prompt simulations across ChatGPT, Gemini, Perplexity, and Google AI Overviews to measure your brand citation share of voice, crawler access, and entity clarity.

  2. Strategic AI Architecture & Entity Roadmap

    Week 3–4

    Turn brand knowledge into machine-extractable authority.

    We define the exact schema hierarchy, llms.txt directives, knowledge graph entities, and content restructuring needed to position your brand as the definitive category answer.

  3. Engineering & Schema Implementation

    Week 5–8

    Zero-fluff technical execution tailored to your CMS and stack.

    We work directly with your engineering and content teams to deploy semantic markup, resolve entity ambiguities, and optimise crawlability for autonomous AI agents.

  4. Continuous AI Monitoring & SOV Expansion

    Ongoing

    Track answer presence, sentiment, and revenue impact over time.

    As foundational models update, we continually benchmark prompt variations, track citation drift, and protect your brand's presence in conversational discovery.

The Numbers I Am Measured By.

Category Search Demand · Top-Four Banking

56% Share of Voice Uplift

BANKING

56% Share of Voice Uplift

Share of voice uplift in one of Australia's most contested search categories, with 58.4% of non-brand keywords in the top five.

Illustrative trend

Read the case study

B2B + B2C

400–600% Organic Traffic Uplift

Organic traffic growth for client pages in competitive niches including alcohol, B2B services and consulting.

Illustrative trend

Read the case study

ECOMMERCE

+250% Client eCommerce Revenue

Client eCommerce revenue growth that won an Omnicom-wide innovation competition.

Illustrative trend

Read the case study

All results

[05]Industries

AI Search by Industry Vertical

How generative engines, LLM shopping assistants, and answer models impact discovery across Australian enterprise sectors.

View all industry verticals

[06]Questions

Frequently Asked Questions

  • Traditional SEO focuses on earning clicks from a list of ranked search results. Generative Engine Optimisation (GEO) focuses on getting your brand accurately cited, summarised, and recommended directly inside generated answers from ChatGPT, Gemini, Perplexity, and Google AI Overviews.

  • AEO structures and validates content so AI models and answer engines can extract direct, unambiguous facts. The primary objective is accurate citation within the response rather than simply a link click.

  • We benchmark query sets across LLMs to track Share of Model (SoM), citation frequency, source attribution URLs, and entity sentiment, giving you a measurable score against category competitors.

  • Large language models reason over entities (people, organisations, products) and their relationships, not isolated web pages. Inconsistent brand data across Wikidata, schemas, and directories confuses models, causing them to omit you from recommendation shortlists.

  • llms.txt is an emerging web standard (similar to robots.txt) that provides a clean, markdown-based summary of your website specifically structured for AI agents and LLM web crawlers.

  • Yes. They are mutually reinforcing. Strong technical foundations, high crawlability, and authoritative content are prerequisite inputs that feed the retrieval-augmented generation (RAG) pipelines powering AI search.

Direct Advisory · 1 Business Day Response

Tell Me What You Need to Win.

I will tell you honestly whether I am the right person for your organic search and AI discovery programme.