Search Marketing for Generative AI

We ensure your brand is not just indexed, but understood, preferred, and selected by the Generative AI ecosystem.

Trusted by Innovative Brands

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Competitive Visibility

See where you stand relative to competitors in the AI's knowledge layer. Understand who gets recommended, and why.

AI Selection Rate

Quantify how often AI systems choose your brand when answering queries in your category. The metric that matters in the generative era.

LLM Brand Sentiment

Analyse how AI models perceive your brand by examining semantic associations in their training data. No guesswork, just observable patterns.

SXO & Semantic Architecture

Optimising site architecture and EEAT signals to provide a crawlable, authoritative base for AI agents.

Entity Optimisation

Strengthen your brand's knowledge graph presence. Clear entity relationships mean consistent AI representation across platforms.

Content Authority Signals

We execute technical and content strategies to build "Machine Trust," ensuring your brand is the cited authority for your core topics.

AI Agent Optimisation

Prepare for the shift from human-driven search to AI-driven transactions by optimising for autonomous agent protocols.

Data Provenance

Verifiable, trustworthy data is the currency of AI commerce. Establish clear provenance chains that agents can validate.

Agentic Protocol Setup

Optimising product data for OpenAI's ACP, Google's UCP, and Anthropic's MCP protocols to ensure "choosability."

Generative Engine Advertising

Prepare the strategic infrastructure needed to leverage paid advertising opportunities within generative AI environments.

AI Advertising Insights

Analyse competitor Ad placements & copy.

Incredible Intent Signals

Ads in ChatGPT and Google's AI Mode offer incredible relevance & customer intent.

From diagnostic to deployment.

How We Work

Deep research in expected Prompt behaviour

step 01

We analyse your target audience to identify high-impact topics and benchmark your current visibility, defining exactly which prompts to track and optimise for maximum and positive Share of Model (SoM).

Learn about our audit
Prompt Research
Prompt Research

We architect your machine-readable foundation

step 02

Based on audit findings, we design a technical architecture that addresses your specific gaps. Schema.org markup, entity optimisation, content structure, everything AI needs to understand you correctly.

Every recommendation is tied to measurable outcomes. No vague 'best practices', just engineered solutions for your identified problems.

See our approach
Architecture Design
Architecture Design

We build and deploy the infrastructure

step 03

Our team implements the technical changes, whether that's structured data, content optimisation, or knowledge graph integration. We work alongside your development team or handle it entirely.

Everything is documented, validated, and tested against real AI model responses before going live.

Our implementation process
Implementation
Implementation

We track Selection Rate long-term

step 04

Post-implementation, we monitor how AI models respond to your optimised presence. Selection Rate, entity accuracy, recommendation frequency; all measured and reported.

This isn't a one-time project. As AI models evolve, we ensure your relevance engineering evolves with them.

Get Started
Measurement
Measurement

What Experts Say About AI Search

The Importance of GEO

The brands that understand how to be 'machine-readable' today will own the AI-mediated customer journey tomorrow. This is the new SEO.
GEO isn't optional anymore. It's existential for brand visibility.
When AI answers questions, it doesn't show ten blue links. It chooses one answer. One brand.
The shift from search to synthesis means brands need to think about being understood by machines, not just indexed. Structured data, entity clarity, and semantic authority are the new ranking factors.

How is this different from traditional SEO?

Traditional SEO ranks pages for human clicks. PromptMarketing optimises for LLM synthesis, ensuring AI models recommend your brand as the "chosen" entity in conversational answers.

What is a "Selection Rate"?

This is our primary KPI. It quantifies how often AI systems choose your brand as the recommended solution when answering category-specific queries.

Can you help with the "Zero-Click" problem?

Yes. We target AEO (Answer Engine Optimisation) to ensure that even when a user doesn't click, your brand is the cited authority providing the answer.

What is an LLM?

Large Language Model, aka AI Chatbot (ChatGPT, Gemini, Google AI Mode, Perplexity, Claude et al.)

What is Prompt Tracking?

Visibility sampling in LLMs.

What is AEO?

Answer Engine Optimisation; target zero-click answer boxes, citations & AI Overviews.

What is GEO?

Generative Engine Optimisation; get mentions in Generative Experiences.

What is AI Search?

Umbrella term for AEO / GEO.

What is Agentic Commerce?

Get your product, service and brand chosen & purchased by agents.

What is MCP?

Model Context Protocol; the infrastructure for the Agentic Web.

What is ACP?

Agentic Commerce Protocol by OpenAI; UCP is Google's variant.

What is GEA?

Generative Engine Advertising; sponsored placements in generative experiences.

Ready to Dominate the New Search Era?

Most brands discover they're invisible to AI, or worse, misrepresented. A GEO Readiness Audit reveals exactly where you stand.

Let's Talk

Ready to become machine-readable?

Contact us to learn how Relevance Engineering can help your brand become AI-ready.