An audit should end with decisions, not a spreadsheet of warnings. Start with the pages that matter commercially, find the constraint that prevents them working, and attach every recommendation to a measurable outcome.
Map the pages that earn attention
List the pages that receive organic impressions, qualified visits, enquiries, or assisted conversions. Compare that list with the pages the business needs to be found for. The gaps are often more valuable than a generic site-wide score.
Group URLs by intent and template. A problem affecting one page type can be fixed once at the owning component or route rather than repeated page by page.
Trace access to understanding
Check status codes, redirects, canonicals, robots rules, XML sitemaps, internal links, duplicate templates, and rendered content. Then inspect whether title, H1, copy, schema, and links agree about the page's subject.
For AI search, record whether the organisation, services, authors, evidence, and locations are described consistently. Ambiguous entities create weak retrieval even when individual pages look polished.
Prioritise by impact and effort
Fix broken access and indexation before rewriting paragraphs. Address slow server responses, oversized critical assets, unexpected layout shifts, and client-side rendering that delays the main answer. Use field data when available and lab data for controlled diagnosis.
Finish with an owner, expected outcome, implementation order, and validation check. Re-crawl after deployment and compare Search Console and analytics data over a sensible period.
A good audit is a route from evidence to action. It makes the important pages accessible, understandable, quick to use, and easier to trust across search journeys.
How often should a technical SEO audit run?
Run a focused audit after major releases, migrations, or template changes, and schedule a broader review often enough to catch drift. The right frequency depends on release volume and site complexity.
Should Core Web Vitals be the first audit priority?
Only when performance is the controlling problem. Broken canonicals, blocked pages, or unclear intent can be more damaging. Prioritise the issue that prevents important pages from being discovered, understood, or used.
What makes an AI search audit different?
It adds entity clarity, source quality, authorship, citation context, answer structure, and representative prompt observation to the normal crawl and page experience checks.
Turn the research into a working plan.
Bring the evidence, constraints, and next decision. We will help you turn it into a clear technical brief.