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[D] Digital Marketing · Block 01 — Hero
Generative Engine
Optimisation
When ChatGPT, Gemini, or Google’s AI Overview answers a question about your industry, your brand should be in the answer.
What’s included
Block 02 — The Problem
AI-generated answers are the new first page. Most brands aren’t on it.
When a user asks ChatGPT which agency to use for SEO in their market, the response draws on which sources are authoritative, well-structured, and frequently cited. Brands that have not built the signals that AI models use to evaluate authority are invisible in these responses — regardless of their traditional search rankings.
Block 03 — Our Approach
Build the signals that LLMs use to identify authority. Specifically and systematically.
Brand entity optimisation: Structure your brand’s digital footprint so AI models can identify, understand, and accurately represent what you do
Citation and reference building: Develop the external mentions, expert citations, and third-party references that LLMs draw on when constructing answers
Content depth strategy: Produce comprehensive, well-cited, expert-level content that generative models pull from when constructing authoritative responses
Structured data layer: Implement schema and structured data signals that help AI models understand your brand’s context, category, and authority
Monitoring and calibration: Track AI Overview appearances, LLM citation patterns, and brand mention frequency in generative responses
Block 04 — What You Get
Brand authority embedded in AI-generated answers across every major platform.
Brand Entity Audit
Analysis of how AI models currently understand and represent your brand
Authority Gap Analysis
Identification of the citation and reference signals your brand is missing
Content Depth Brief
A plan for the expert-level content that positions you as an LLM-cited authority
Schema and Structured Data
Technical implementation to clarify brand context for AI interpretation
GEO Monitoring Report
Ongoing tracking of generative engine appearances and citation frequency
Block 05 — Cost of Delay
LLM training data has a cutoff. Brand authority built now influences model outputs for years.
The brands that establish authority signals now are building into the training data sets that will influence AI responses for the next model generation. Early movers build compounding authority that becomes structurally difficult to displace.
The GEO window is narrowing. A conversation costs nothing.
One strategy session maps where your brand currently appears in generative engine responses and what it would take to be in the answers your prospects are reading.