About Me

My path into SEO wasn’t a straight line, and I think that’s what makes the way I work different. Over 15 years in online marketing, management, and sales, I’ve built a set of skills that don’t usually sit in the same person – and in SEO, that breadth genuinely matters. Before I ever opened a keyword research tool, I was working in sales and management: negotiating corporate contracts, leading teams, managing client relationships, and running operations across the hospitality and travel industries. Later, I co-founded MINDESI – a vegan shoe brand – where I ran everything from the Kickstarter campaign and website build to supply chain negotiations and paid advertising. That combination of corporate sales experience and hands-on entrepreneurship gave me something that’s hard to learn from SEO courses alone – an instinct for how businesses actually work, what decision-makers care about, and how to connect a technical recommendation to a commercial outcome. When I talk to stakeholders about organic performance, I’m not translating SEO into business language. I already think in both.

A Deliberate Move Into SEO

After MINDESI, I made a deliberate decision to pursue it professionally – not as a generalist, but going deep into SEOspecifically.

Since then, I’ve grown from SEO Trainee to Senior SEO Manager, taking full end-to-end ownership of SEO strategy across a portfolio of brands spanning different product categories and markets. My day-to-day work covers the full SEO stack: on-page optimisation and content strategy, technical SEO audits and monthly crawl monitoring, Core Web Vitals and PageSpeed analysis, schema markup implementation, tracking setups in GTM and GA4, SEO dashboards in Looker Studio, workflow automation with n8n, and increasingly GEO and AIO – optimising content to be retrieved and cited by AI systems such as Google AI Overviews and ChatGPT. Alongside the SEO work itself, I take on a project management role, coordinating between development, content, and design teams to get recommendations actually implemented. The most concrete result of that work is a 400% increase in the Visibility Index of one of the brands I manage (source: SISTRIX) – the result of several parallel technical and content workstreams, not a single fix. It’s the kind of outcome that only comes from understanding the full picture: crawl architecture, Core Web Vitals, topical authority, content strategy, and tracking, – all working together.

Where My Focus Is Now

What the sales background, the entrepreneurial chapter, and six years of hands-on SEO work have in common is that they all required the same thing: understanding what people actually want, and then building something that meets them there. In SEO terms, that means I work at the intersection of three things equally.

  1. AI systems don’t rank URLs – they generate answers. Tools like ChatGPT, Perplexity, and Google’s AI Mode decide what to cite through grounding, RAG (Retrieval-Augmented Generation), and Query Fan-Out: a prompt is decomposed into multiple sub-queries, results are retrieved across several indexes, re-ranked using methods like Reciprocal Rank Fusion, and synthesised into a final answer. A page needs to appear consistently across enough of those sub-queries to make it into the output.
  2. Each system behaves differently, which changes what’s worth tracking:
    • Google AI Mode and Perplexity ground almost every query by default.
    • ChatGPT decides dynamically whether to retrieve external sources at all.
  3. The work is optimisation plus custom measurement. That means optimising content to be cited in AI-generated answers and building tracking to measure it – including a GTM-based AIO snippet tracking implementation that captures the exact snippet text Google serves from a page in AI Overviews, using custom JavaScript variables to extract the text from the URL fragment and firing it as a GA4 event filtered to question-type queries, alongside RegExp patterns in Google Search Console to isolate AI Overview-driven query data and visualise it in Looker Studio dashboards.
  4. I automate recurring SEO processes – keyword research, bulk SERP scraping, technical monitoring, and reporting – using n8n workflows, so working time goes into analysis rather than manual data assembly. I work within a circle of SEO specialists where problems get tested against other practitioners’ experience, follow Claneo Academy, OMR, SEO Südwest, Lily Ray, and Google Search Central as standing sources, and attend live seminars from SEO experts to stay close to where the field is moving.
  5. The fundamentals haven’t changed. Based on what SISTRIX data confirms, technical cleanliness, genuine topical authority, and high-quality content remain the primary levers – chasing AI-specific tactics without getting those right first is a dead end. The difference now is that the same foundations need to perform across classical search and AI retrieval simultaneously, and the bar is higher: AI systems retrieve sources that demonstrate real expertise and consistency across a topic, not just pages that rank well for a single query.