Technical SEO Analyst

David Brauksworth

“Measure what is measurable, and make measurable what is not so.”
Galileo Galilei

David Brauksworth, Technical SEO Analyst at KatvTech

David Brauksworth approaches SEO from the infrastructure level up. His background in web performance engineering means he was optimising load times, server response rates, and rendering pipelines long before Core Web Vitals became a confirmed ranking factor. At KatvTech he runs all experiments measuring the relationship between technical site health and search visibility outcomes.


How David approaches technical SEO research

Most technical SEO advice exists in one of two forms. The first is theoretical: here is what Google says matters and here is why it should affect rankings. The second is anecdotal: here is what happened on one site after one change. David is interested in a third form, controlled measurement over defined periods with documented conditions and explicitly stated limitations.

His background in web performance engineering gave him both the technical foundation to implement precise changes and the professional habit of measuring outcomes before declaring success. In performance engineering, a deployment that improves load time on one device type while degrading it on another is not a success. The same precision applies to his SEO experiments. A technical change that improves Core Web Vitals scores without producing a measurable ranking change within a defined window is documented as such, not reframed as a long-term investment with unmeasurable benefits.


What David focuses on at KatvTech

David leads all experiments in the technical SEO dimension of KatvTech’s research programme. His specific areas of focus are:

  • Core Web Vitals as ranking factors. Measuring whether and how quickly improvements to LCP, INP, and CLS produce observable ranking changes, and under what conditions the relationship is strongest.
  • Composite CWV scoring impact. Following the March 2026 update that introduced aggregated scoring, David is running experiments to determine how the composite model changes the relative importance of each individual metric.
  • Indexing speed and crawlability. What hosting configurations, sitemap structures, internal linking patterns, and technical implementations affect how quickly new content on new domains gets discovered and indexed.
  • Theme and plugin performance impact. Measuring the ranking implications of specific WordPress theme and plugin choices, particularly for sites using heavy page builders that consistently produce poor INP scores on mobile.

David on technical SEO in 2026

The technical SEO conversation in 2026 has a tendency to conflate two different things: technical health as a prerequisite for ranking, and technical improvements as a mechanism for gaining ranking. These are not the same claim and they do not have the same evidence behind them.

A site with fundamental technical problems, broken crawlability, failed Core Web Vitals, no sitemap, blocked resources, will struggle to rank regardless of content quality. Fixing those problems removes a barrier. It does not guarantee a ranking gain. The question David finds more interesting is the marginal one: on a site that is already technically functional, how much does a measurable improvement in a specific technical metric move rankings, on what type of content, over what time period, under what competitive conditions?

That question does not have a clean universal answer. David is building the dataset that makes a more specific answer possible.


Experiments led by David Brauksworth

David authors all experiments in the technical performance dimension of KatvTech’s Ranking Experiments category. Each article follows KatvTech’s standard five-part methodology and includes the specific technical conditions, hosting environment, and measurement tools used in each test.

Technical suggestions and experiment proposals can be submitted through the contact page. David prioritises proposals that include a specific measurable hypothesis and a practical implementation context.

See Posts from David

AI Overviews Optimization: What Actually Earns Citations

AI Overviews now appear on a meaningfully large and growing share of Google searches, and getting cited inside one requires a different playbook than climbing the traditional ten blue links. AI overviews optimization is close cousin to classic SEO, sharing much of its…

How to Track Brand Mentions in ChatGPT Reliably

You cannot improve what you cannot measure, and knowing how to track brand mentions in ChatGPT reliably is genuinely harder than checking a classic ranking position. Here is how to track brand mentions in ChatGPT with the methods currently available, and an honest…

LLM Rank Tracking Tools: What’s Actually Available Now

Classic SEO has Search Console and two decades of rank tracking infrastructure behind it. Measuring visibility inside AI-generated answers has none of that maturity yet, which is exactly why the current crop of llm rank tracking tools matters and why none of them…

GPTBot: What It Is and How to Control Its Access

Every AI SEO strategy assumes a site is actually reachable, and GPTBot is the specific crawler determining whether that assumption holds true for OpenAI’s systems. Understanding what it does, and how to deliberately allow or block it, is a prerequisite most content…

ChatGPT SEO: How to Get Cited Instead of Ignored

ChatGPT SEO gets treated as a mystery box by a lot of the industry, when in practice its sourcing behavior is more documented than most people realize, just genuinely different from what classic SEO trains you to expect. How ChatGPT Actually Sources Information…

Conversational Search Optimization: The Basics

Someone types “best running shoes” into Google. The same person asks an AI assistant “I have flat feet and run about 20 miles a week, what shoes should I actually get, and are they worth the extra cost over a cheaper pair.” Conversational search optimization exists…

Knowledge Graph Optimization: Building Entity Trust

Google stopped matching keywords a long time ago. It matches entities, people, places, organizations, concepts, and the relationships between them, and that shift is exactly what knowledge graph optimization is built around: being recognized as a clear, consistent…

Perplexity SEO: How Its Citation System Actually Works

Perplexity operates differently from both Google and ChatGPT in a way that changes what optimization actually means for it. Rather than relying primarily on a pre-built index or a licensed search partner, Perplexity performs real-time retrieval against its own index…

LLM SEO: How to Get Cited by ChatGPT and Perplexity

Traditional SEO chases a click on one of ten blue links. LLM SEO chases something narrower and, in some ways, harder to win: a named citation inside an AI-generated answer that the reader may never click through to verify. That shift changes what “ranking well” even…