Technical SEO, Answer Engine Optimisation and Generative Engine Optimisation for businesses that want to be easier to discover, understand and recommend across Google and AI-powered search.
I combine technical website analysis, content structure, search intent, structured data and entity clarity so websites are easier for search engines, users and AI systems to understand.
Crawlability, indexation, canonicals, redirects, metadata, sitemaps, internal linking and technical search foundations reviewed against the real website.
Question targeting, direct-answer structure, semantic clarity and information architecture designed to make important answers easier to identify and extract.
Entity clarity, evidence-rich content, expert attribution, topic relationships and source-ready information designed for AI-assisted discovery.
Schema planning and JSON-LD implementation for relevant organisation, service, article, breadcrumb, FAQ and other supported entity types.
Keyword and intent mapping, service-page structure, internal linking, topical clusters and page hierarchies built around how people actually search.
Evidence-based website reviews that separate confirmed findings from recommendations and turn issues into a prioritised implementation roadmap.
They overlap, but each focuses on a different part of how information is discovered, interpreted and surfaced.
Build the technical and content foundation required for traditional organic search visibility.
Structure information so important questions can be understood and answered clearly.
Strengthen how organisations, expertise and information are represented for generative systems.
Search work should move from evidence to action, not from assumptions to generic recommendations.
Review the website, CMS, crawl/index signals, page structure, content, entities and important visitor journeys.
Analyse search intent, competitors, topics, entities, questions and the relationship between demand and business priorities.
Address priority technical, content, schema, internal-linking, AEO and GEO opportunities in a controlled order.
Retest what changed, validate structured data and important website functions, and document remaining priorities.
A transparent portfolio showing personal, independent and demonstration work without presenting uncommissioned projects as client engagements.
A good audit should make the next action obvious. These are the types of practical outputs I structure search work around.
Crawlability, indexation, canonicals, redirects, metadata, internal links, sitemaps and technical issues documented with priorities.
Queries grouped by user intent, page purpose, funnel stage and business relevance.
Important user questions mapped to the pages and answer structures best suited to address them.
Organisation, people, services, locations, expertise and supporting evidence organised into clear relationships.
Recommended Schema.org types, page-level requirements and JSON-LD implementation priorities.
Corrections and improvements ordered by urgency, business impact, dependency and implementation effort.
I prefer verifiable findings, clear priorities and implementation evidence over invented performance promises.
Findings should be tied to what can actually be observed on the website or in available data.
Prioritise issues that affect discovery, enquiries, transactions, trust and important visitor journeys.
Confirmed problems and strategic recommendations should not be presented as the same thing.
Technical and content changes need verification after implementation, not just a completed checklist.
Strong search architecture should improve clarity for visitors while making information easier for systems to interpret.
I specialise in SEO, Answer Engine Optimisation and Generative Engine Optimisation for businesses that want stronger visibility across traditional and AI-powered search.
My approach combines technical website analysis, search intent, content architecture, structured data, entity optimisation and evidence-based implementation.
I focus on practical improvements: making websites easier to crawl, easier for users to understand and easier for answer and generative systems to interpret accurately.
My work covers website audits, CMS implementation, technical SEO, structured data, AEO content architecture and GEO visibility strategy.
The exact stack depends on the project. I work across search, CMS and technical implementation environments.
Clear definitions matter because these disciplines overlap but are not identical.
SEO focuses on organic search discovery and technical/content foundations. AEO focuses on structuring information so answer systems can identify and surface direct responses. GEO focuses on entity clarity, evidence, authority and content structures that support generative and AI-assisted discovery.
No. GEO usually depends on the same strong technical and content foundations that support SEO. A website that is difficult to crawl, poorly structured or unclear about its entities is unlikely to have a strong foundation for generative visibility.
The scope can include technical search foundations, content architecture, search intent, internal linking, structured data, entities, answer opportunities, expert attribution and evidence/source signals. Findings should then be prioritised into an implementation roadmap.
Structured data can make explicit information about organisations, people, services, articles, breadcrumbs and other entities more machine-readable. It does not guarantee rankings or AI citations, but it can improve semantic clarity when implemented correctly.
No. Search engines and generative systems control their own ranking, retrieval, citation and answer-generation processes. GEO improves the quality, clarity, evidence and structure of the information those systems can evaluate.
Send me the website and the main visibility problem you want reviewed. I can start with the public site and identify the highest-priority search and implementation opportunities.