Dan Petrovic

Dan Petrovic is Managing Director of DEJAN and one of the few practitioners who investigates search systems directly rather than inferring their behaviour from results. His method is to establish how a system works, then apply the finding to technical SEO and large scale optimisation. He has conducted original research into Google ranking systems, user behaviour as a ranking signal, and how people consume online content.

His technical work covers crawling, indexing, SERP features and Google Discover. Google has twice given him an award for discoveries involving APIs that exposed parts of its internal systems, and he identified and reported a core search and ranking security issue that Google subsequently patched. Very few people outside Google have found something Google had to fix. His wider research covers contextual link analysis and organic link earning, supported by experiments designed to establish repeatable relationships rather than one off observations.

Petrovic now applies the same discipline to AI search, examining how models represent brands and how those representations govern visibility in generative results. He uses mechanistic interpretability to inspect what a model has actually encoded, and model steering experiments to test whether the output can be influenced. It is a genuinely technical line of enquiry, and it connects to his earlier work on natural language interfaces and Google’s move towards conversational search.

He has presented at SMX, MozCon, SEO Week New York and Semrush Spotlight, and delivers advanced workshops and industry training. He holds a long association with Griffith University through guest lectures and advisory work. His published research has been recognised internationally, including a place in Moz’s top ten content of the year.