Working together
You work directly with me
From the first conversation, you deal with me. I go through the data and propose the next steps. During implementation, I fix what I can myself and agree with your team on anything that needs development. Afterward, I check the changes and their results.
There are three ways I usually come in:
- Your marketer needs specialist support. They run the day-to-day marketing, but technical SEO, measurement or AI visibility needs separate attention. That’s where I come in, and we talk through what’s worth changing and why.
- You have a team or an agency. I join their work on a specific task: finding technical SEO problems, getting measurement right, or improving AI visibility.
- You’re an agency. I fit into your process, and you keep the client relationship. When it helps, I join the specialist discussions too.
The cost of the model
I take a small number of clients at a time. That’s not scarcity marketing, it’s arithmetic: the model only works while I can hold every client’s system end to end. If the work needs more capacity than I can give it, I’ll tell you at the start.
How I think
How I think about the work
Measurement before strategy
I don’t start with best practices. I start with what the data says and what it can’t yet tell us. If the numbers were never checked against reality, everything built on them is a guess with a decimal point.
One system, not four channels
Search, AI visibility, conversion and measurement are the same problem from different angles. Optimizing one in isolation usually makes another worse: traffic that arrives for the wrong reason, a page that ranks and doesn’t sell, a dashboard that measures neither.
Business numbers, not proxies
Rankings are diagnostics. Impressions are noise. The question is whether revenue moved, and whether the change I made is the reason.
Honest about what I can’t attribute
Some results can’t be traced cleanly to one change. When that happens I say so, rather than claiming the number. It’s a smaller promise and it’s the one that survives contact with your finance team.
AI as an accelerator, not a decision-maker
I use AI for pattern detection, anomaly checks and quality control across large datasets. The business judgement stays human, and it stays grounded in your data rather than a general model’s opinion.
Anti-fit
What I won’t do
A generic audit report
I won’t hand over a long checklist of best practices. You can order the audit on its own: you get a prioritized action plan with specific recommendations, and the reason behind each change.
Guaranteed rankings or guaranteed citations
Nobody can promise either honestly. In AI search especially: systematic reviews of the field report wide variability across platforms and repeat runs, with no strong evidence that any single technique produces stable improvement. Anyone selling certainty there is selling something they can’t deliver.
Work on a site that can’t change
Most of what I find needs structural fixes, not additions. If the answer to every recommendation is “we can’t touch that”, we’ll both waste money — yours faster than mine.
If the site itself is the constraint, that’s a different job, and one I can take on. Execution.
Results this quarter
Trustworthy measurement takes weeks before it says anything. The first fixes ship early; the proof that they worked doesn’t.
Growth for an offer that isn’t there yet
Organic growth amplifies demand. It doesn’t create it. If the product hasn’t found anyone yet, the honest advice is to spend the money elsewhere first.
Social, influencer and PR work
Not my field. This is organic search, AI visibility, conversion and measurement. For the rest I’m the wrong person, and I’d rather say it now than three months in.
Background
I think I was hooked before I even knew what SEO was.
Sometime in the second half of the 1990s, I was driving in Hungary when I heard someone talking about the internet on the radio. I don’t remember the exact program or what they said, but I remember the feeling: this was going to change things, and somehow I wanted to be part of it.
Not long after, I was working for an internet company. That led me to a high-traffic classified site, and later to one of Hungary’s largest news websites. By then, I was working almost entirely on SEO. Search was still a much less mature discipline, which was probably part of what made it so interesting to me: there was no perfect playbook. You had to observe, experiment, compare results and figure out what the search engines were actually doing.
That suited me. I’ve always enjoyed reverse engineering systems — understanding why something works, why a competitor is doing better, or why the numbers don’t behave as expected. SEO turned that curiosity into a profession, and over the years I moved between companies, my own businesses and consulting. The projects changed, Google changed, and eventually search itself expanded beyond Google, but one thing stayed the same: I was always looking for a problem worth solving.
At some point, SEO alone stopped being enough. I had seen websites gain traffic without gaining customers, pages rank without persuading anyone, and teams make decisions from data they couldn’t fully trust. The interesting question was no longer simply how to get more organic traffic, but how the whole system worked together: search, user behavior, conversion, measurement, technology and, more recently, AI visibility.
That’s what organic growth means to me today. SEO is still at the center of it, and I still enjoy trying to understand how search systems work, but the puzzle is bigger now. After more than two decades on the internet, that’s probably why I’m still here: the systems keep changing, and there is always something new to figure out.
Hands-on
Background
What I do hands-on
I write my own SQL, build my own dashboards, and implement directly in Shopify, WordPress and WooCommerce when the work requires it. These aren’t tools I supervise — they’re tools I use daily to answer specific questions. This site is one of them: rebuilt from WordPress, including the measurement and the checks that keep it honest.
Analytics & data: GA4 · BigQuery · Looker Studio · Google Search Console · Bing Webmaster Tools
Behavior: Microsoft Clarity · Hotjar · Cloudflare log analysis
Search & GEO: Screaming Frog · log file analysis · Ahrefs · DataForSEO
Implementation: WordPress · WooCommerce · Shopify · Astro · Cloudflare Workers · GitHub-based deploys · Google Cloud Platform · Jira
Credentials
Certifications and formal training
Verified credentials across generative AI, data analytics, digital marketing and SEO. The primary expertise is hands-on; the training gives it a structured foundation.
| Credential | Issuer | Awarded |
|---|---|---|
| IBM RAG and Agentic AI Professional Certificate — verify (opens in a new tab) | IBM Skills Network · Coursera | March 2026 |
| AI SEO: Mastering Generative Engine Optimization (GEO) — verify (opens in a new tab) | SkillUp · Coursera | March 2026 |
| Generative AI Leader — verify (opens in a new tab) | Google Cloud Training · Coursera | January 2026 |
| Google Data Analytics Professional Certificate — verify (opens in a new tab) | Google Career Certificates · Coursera | May 2023 |
| Google Digital Marketing & E-commerce Professional Certificate — verify (opens in a new tab) | Google Career Certificates · Coursera | May 2023 |
| Machine Learning Operations (MLOps) for Generative AI — verify (opens in a new tab) | Google Cloud Skills Boost | February 2026 |
| Google Cloud Fundamentals: Core Infrastructure — verify (opens in a new tab) | Google Cloud Skills Boost | October 2023 |
| SEO Certification — verify (opens in a new tab) | HubSpot Academy | — |
Next step
Not sure whether I’m the right person?
Send me your URL and one sentence about what isn’t working. I’ll tell you where I’d look first, and whether I think it’s worth your money to have me look at all. No pitch, no discovery-call ritual.