THE METHODOLOGY
How AI recommendation infrastructure works.
Three components. One outcome. Getting recommended by AI when a buyer asks.
THE SHIFT
AI is not Google. Stop optimising for the wrong system.
Google ranks pages. AI selects answers. Google optimisation is about signals, backlinks, and crawl priority. AI recommendation is about structured authority - whether AI has enough reliable, structured information about your business to recommend you with confidence. Most businesses have optimised for search and done nothing for recommendation. That is the gap we close.
THE EVALUATION
What AI is looking for when it makes a recommendation.
01 STRUCTURED KNOWLEDGE
AI needs well-organised content that directly answers buyer questions. Most business websites are built for humans browsing, not for AI evaluating.
02 CONSISTENT AUTHORITY
AI cross-references multiple sources. Inconsistent business information across directories and platforms creates uncertainty that costs you the recommendation.
03 VERIFIABLE PROOF
Reviews, credentials, case studies, and certifications are not just trust signals for humans. They are the evidence layer AI requires before recommending with confidence.
04 TECHNICAL READINESS
AI crawlers read your digital presence differently from search engines. Structured data, schema markup, and page architecture determine whether AI can parse what you offer.
THE METRIC
Your Recommendation Score: four signal layers, one number.
Knowledge Centre Health
Measures whether your AI Knowledge Centre contains the structured content AI needs to evaluate and recommend you. Assessed across content coverage, content depth, schema implementation, and citation readiness.
70+ indicates strong structured content coverage with well-implemented schema.
Directory Consistency
Measures whether your business information is consistent across the directories and platforms AI references. Inconsistencies reduce recommendation confidence.
75+ indicates consistent NAP data and service descriptions across major directories.
Proof Layer
Measures the strength of your evidence layer including reviews, credentials, case studies, and certifications.
65+ indicates a strong proof layer with diverse evidence types.
Technical Readiness
Measures whether your digital infrastructure is structured for AI crawler access including schema markup, page architecture, and content accessibility.
70+ indicates well-structured technical infrastructure for AI access.
THE KNOWLEDGE CENTRE
What your AI Knowledge Centre contains.
THE TRACKING
We test every week. Across four platforms.
Our tracking system runs your business through a defined set of buyer queries every week across ChatGPT, Claude, Gemini, and Perplexity. It records whether you are recommended, how you are described, and which competitors appear. Your Recommendation Score updates weekly. You see the movement.
Get Your Recommendation Score
Get StartedFrequently Asked Questions
You complete a short onboarding questionnaire. We run your baseline Recommendation Score across ChatGPT, Claude, Gemini, and Perplexity. You receive a full gap analysis. We then build your AI Knowledge Centre, typically live within 10 business days.
An AI Knowledge Centre contains service pages structured to answer specific buyer queries, FAQ content mapped to buyer questions, comparison pages including when competitors win, a proof and evidence layer including reviews and credentials, location and service area pages, and comprehensive schema markup and structured data.
The Recommendation Score is updated weekly. Our tracking system runs a defined set of buyer queries through ChatGPT, Claude, Gemini, and Perplexity every week. It records whether your business is recommended, how it is described, and which competitors appear. Results feed into four sub-score calculations and the composite score updates.
Knowledge Centre Health measures whether your AI Knowledge Centre contains the structured content AI needs to evaluate and recommend you. It is assessed across content coverage, content depth, schema implementation, and citation readiness.