SEO & AI Search Visibility

Technical SEO determines whether search engines can crawl, render, and index your site efficiently. Most of it lives in code and server configuration, which is why audits from non-developers often end as PDF reports nobody implements. When I find an issue, I fix it in the same pass.

I crawl the site with Screaming Frog, cross-check against Google Search Console, and work through indexation, redirects, canonicals, duplicate content, and architecture. Because I administer VPS servers, the fixes extend below the CMS: server response times, caching, compression, SSL configuration, and clean redirect handling at the server level.

• Crawlability and indexation: robots.txt, XML sitemaps, noindex conflicts, orphaned pages
• Site architecture: logical hierarchy, shallow crawl depth, sensible URL structure
• Core Web Vitals: LCP, INP, and CLS fixed in the code, not masked with plugins
• Redirects and canonicals: chains removed, duplicate content consolidated
• Server layer: response times, HTTPS/SSL, caching headers, compression

Keyword research is about intent, not volume. I use SEMrush, Ahrefs, Moz, and Ubersuggest to find the queries your buyers actually type, then map one primary intent to each page. A page that tries to rank for everything ranks for nothing.

On-page work follows the map: titles and meta descriptions written for relevance and click-through, one clear H1 per page, heading hierarchies that mirror the content's logic, and alt text that describes instead of stuffing. Internal linking gets particular attention — it is how authority flows through a site and how search engines learn which pages matter most.

Schema markup is structured data that tells search engines exactly what a page is: an organization, a service, a product, an article, an FAQ. I write it in JSON-LD, match it to what is visibly on the page, and validate it before it ships. Mismatched or exaggerated markup does more harm than none.

Entities matter as much as keywords now. Your business name, services, location, and authorship should be identical everywhere they appear — on the site, in the schema, and across external profiles. Consistent entity data is what lets Google and AI systems connect your pages to a single, trustworthy source.

A growing share of searches now ends in an AI-generated answer — Google's AI Overviews, ChatGPT, Perplexity — instead of a list of links. These systems synthesize responses from sources they can parse and verify, then cite them. Being citable is the new version of ranking, and it is earned through structure, not tricks.

AEO (answer engine optimization) and GEO (generative engine optimization) are the practices behind that. I adopted them early in client work, and they are part of every SEO engagement I take on, not an add-on.

The good news: AEO builds on classic SEO rather than replacing it. A site that is fast, well-structured, schema-rich, and entity-consistent is already most of the way there. What changes is the writing — direct, factual, and organized so a machine can lift an answer without misquoting you.

• Direct answers in the first sentence of each section, elaboration after
• Headings phrased as the questions people actually ask
• Facts stated once and kept consistent everywhere they appear
• FAQ and article schema where it genuinely applies to the content
• Clean, semantic HTML that machines can parse without guessing

Every engagement runs on Google Search Console and GA4, configured properly rather than left on defaults. I monitor indexation coverage, query impressions and positions, Core Web Vitals, and the conversions that matter to your business. You see the same data I see.

What I will not do is guarantee rankings or dress up vanity metrics. If something is working, the data will show it; if it is not, I will say so and adjust. That is the standard you should hold anyone doing SEO to — developer or agency.