Why a site can rank poorly even with great content
A page can be well-written, fast to load in a browser, and still be invisible in search results because of something entirely unrelated to content quality: a rogue canonical tag pointing to the wrong URL, a JavaScript framework that renders the main content client-side after Googlebot has already given up, a robots.txt rule blocking CSS files, or a sitemap that still lists three thousand URLs from a migration that happened two years ago. Technical SEO is the discipline of finding and fixing these mechanical barriers between your content and the search engine's index. It has nothing to do with keyword density or meta description length - it's closer to systems debugging than copywriting.
What the audit actually looks at
Crawlability and log files
We pull raw server log files (Apache/Nginx logs or CDN logs from Cloudflare, Akamai, etc.) and separate genuine Googlebot and Bingbot hits from spoofed user agents. This tells us which sections of the site are actually being crawled, how often, and which pages are being ignored entirely. It's a far more reliable signal than Search Console's sampled crawl stats. From there we look at crawl budget waste - faceted navigation generating thousands of parameterised URLs, session IDs in URLs, infinite calendar pages, or internal search results pages that got indexed by accident.
Indexation and canonicalisation
We audit canonical tags, hreflang implementation for multi-region sites, pagination handling (rel=next/prev is largely deprecated but the underlying crawl-path problem it solved still exists), and noindex/robots directives across templates. A common finding: staging subdomains or old category templates still indexed and competing with the live pages for the same query.
Rendering and JavaScript SEO
For React, Vue, Angular or Next.js front ends, we check whether critical content and links are present in the initially rendered DOM or only appear after hydration. We use Google's URL Inspection tool and a headless Chrome render comparison to spot cases where the rendered HTML Googlebot sees differs from what a user sees. Where server-side rendering or static generation isn't already in place, we recommend the specific rendering strategy (SSR, SSG, or dynamic rendering as a fallback) rather than a blanket "switch frameworks" suggestion.
Site speed and Core Web Vitals
We measure LCP, CLS and INP using both lab data (Lighthouse, WebPageTest) and field data (CrUX report, if traffic volume allows). Fixes are usually specific: deferring non-critical JavaScript, preloading the LCP image or font, eliminating layout shift from ad slots or web fonts, compressing and correctly sizing images, and reducing third-party script bloat from tag managers that have accumulated years of unused tracking pixels.
Structured data
We implement schema.org markup in JSON-LD - Product, Article, FAQPage, BreadcrumbList, LocalBusiness, Review/AggregateRating, Organization - matched to what the page actually contains, validated against Google's Rich Results Test rather than just schema.org's generic validator, since Google enforces its own subset of eligibility rules for rich snippets.
Common triggers for this kind of engagement
- Organic traffic dropped after a site migration, replatforming, or a switch to a new CMS/framework
- A large catalogue or blog where most pages simply never get indexed
- Search Console shows a growing "Crawled - currently not indexed" or "Discovered - currently not indexed" count
- Core Web Vitals report in Search Console is flagging a large share of URLs as "Poor" or "Needs improvement"
- An international site with hreflang errors causing the wrong country version to rank
- A JAMstack or SPA rebuild that looks fine to users but returns near-empty HTML to crawlers
How we scope and deliver the work
We start with access - Search Console, Analytics, log files, a staging environment if one exists - rather than a generic checklist audit, because the real constraints of a site only show up once you can see its actual crawl behaviour and code. The audit output is a prioritised list ordered by estimated impact versus implementation effort, not a 60-page report of every theoretically possible issue. Items are grouped into what can be fixed via CMS configuration, what needs a template or code change from a developer, and what needs a decision from the business (e.g., whether to merge or redirect a set of overlapping category pages).
Implementation is done either by our team directly in the codebase/CMS, or handed to the client's development team with exact specifications - which tag, which value, which template - since vague recommendations like "improve site speed" are where most technical SEO work stalls in practice.
What we don't promise
Technical SEO fixes remove barriers to ranking; it doesn't manufacture demand or make thin content competitive. We're explicit with clients when an indexation or speed problem is capping performance, versus when the real gap is content depth, backlink profile, or topical relevance - those need separate content and outreach work, and we say so rather than selling a technical package as a cure for everything.
Reporting and post-launch checks
After fixes ship, we re-crawl the site with Screaming Frog or Sitebulb to confirm the specific issues are resolved (not just "SEO score improved" in some third-party tool), monitor Search Console's Index Coverage and Core Web Vitals reports over the following weeks, and check log files again to confirm crawl behaviour actually changed. Regressions are common when a new template or plugin ships without SEO review, so we typically set up an ongoing lightweight monitoring check rather than treating the engagement as a one-time audit.
