AI-assisted SEO analysis
AI-assisted SEO analysis turns crawl, search and competitor data into a prioritised list of actions.
Background
Search Console, crawlers, rank trackers and log files supply plenty of SEO data. The bottleneck is analysis. AI condenses thousands of URLs and search terms into a short list: what should change, why, and at what effort. People with SEO experience decide what gets done.
What the analysis delivers
Keyword clusters: embeddings group search terms by meaning, exposing topic gaps and cannibalisation.
Content gaps: questions that ranking competitor pages answer and yours do not.
Technical findings: status codes, redirects, canonicals, structured data and Core Web Vitals from Chrome UX Report field data, sorted by impact.
Log file analysis: which pages Googlebot really visits and where it wastes crawl budget.
Internal linking: suggested links between related pages.
AI Overviews and chat assistants
Google shows AI Overviews for many queries, and some research now happens in chat assistants. We therefore check that your content is quotable and machine-readable: clear headings, schema.org structured data and clear details about your company and authors.
From finding to action
Data: Search Console, analytics and a full crawl.
Analysis: clustering, competitor comparison and a technical review.
Action list: each recommendation with rationale, effort and expected impact, by priority.
Implementation: technical changes directly in Statamic, Laravel or Shopify, content changes as briefs for your editors.
Measuring progress
We agree the metrics up front, such as Search Console clicks, positions per topic cluster or organic enquiries. We review them with you regularly in a shared dashboard.
Because SEO works with a delay, we assess changes over several months and, where possible, separate them from Google updates and seasonal effects.