Start with the questions your audience is trying to answer
AI-search measurement becomes noisy when it begins with a generic list of prompts. I start with audience needs, commercial journeys, products, entities and decisions. That produces a prompt set with a reason to exist and a baseline that can support action rather than decorate a dashboard.
The work can cover Google AI features, conversational assistants and other relevant discovery environments. The goal is not a single universal score. It is to understand where the organisation appears, how it is represented, what evidence is being selected and where competitors have an advantage.
Investigate visibility as a system
Owned pages are one part of the evidence available to AI systems. Reviews, publications, communities, reference sources, product information and established entities can all affect what is retrieved and how an organisation is described.
- Prompt and journey coverage
- Brand inclusion, recommendations and descriptive accuracy
- Cited domains and source patterns
- Competitor visibility and message differences
- Crawlability, indexability and textual availability of important information
- Entity consistency and supporting third-party evidence
- Content gaps where the organisation has genuine expertise to contribute
Build a programme that can survive platform change
AI interfaces, models and measurement products will continue to change. A useful strategy therefore separates durable foundations from platform-specific experiments. Clear information, strong evidence, accessible pages, reputable references and disciplined measurement remain useful even when an interface changes.
I help teams define ownership, review cycles, reporting limitations and the threshold for acting on new observations. That turns experimentation into a managed capability instead of a sequence of disconnected tactics.
Strategy, enablement and implementation guidance
An engagement can end with a strategy and roadmap, continue into implementation guidance, or include workshops that help content, PR, product and SEO teams understand their role. The delivery is remote and designed to fit established teams rather than replace them.
What you receive
- A clear definition of the audiences, journeys and prompts worth measuring
- A baseline across agreed AI-search environments and traditional search evidence
- Analysis of citations, sources, entity interpretation and competitor presence
- A prioritised strategy across owned content, technical foundations and third-party signals
- Measurement and reporting guidance that the team can repeat
- Remote workshops for stakeholders, content teams and specialists
What the work is designed to change
- A shared understanding of what AI-search visibility means for the organisation
- Less time spent chasing speculative tactics
- A measurement system connected to useful commercial questions
- Priorities that strengthen both conventional and AI-assisted discovery
Common questions
Is AI SEO different from traditional SEO?+
The interfaces and measurement questions differ, but many foundations overlap: crawlable and useful content, clear entities, reliable evidence, strong reputation and good technical implementation. AI-search consultancy adds prompt research, citation analysis, representation checks and cross-platform measurement.
Can you guarantee that an AI system will recommend our brand?+
No responsible consultant can guarantee a recommendation from a probabilistic system operated by another company. I can establish the evidence, identify weaknesses, improve eligibility and relevance, and build a repeatable way to measure change.
Do we need specialist GEO software?+
Not always. Tools can make repeated monitoring easier, but the right prompt set, sampling method and interpretation matter first. I can help evaluate products or design a practical baseline with the resources already available.