Teaching & Research
Teaching the part that usually gets skipped.
More than 700 hours delivered in analytics, AI-driven personalisation, performance marketing and consumer behaviour, to postgraduates and to working professionals who bring their own live problems into the room.
My bias as a teacher is towards instruments over illustrations. If a concept can only be explained, it probably has not been understood. So the courses run on live platforms and real briefs, and where the right tool did not exist I built it.
What I teach
Five subjects, one argument.
The argument being that marketing decisions are economic decisions, and that a marketer who cannot read the commercial side of a campaign is guessing with someone else’s money.
Analytics and measurement
GA4 from implementation through to interpretation, data streams, events, dimensions and metrics, customer journey analysis, and building reports that answer a business question rather than fill a slide.
Programmatic advertising and real-time bidding
Auction logic, bidding strategy and automated buying, taught through simulation so that participants can make expensive mistakes cheaply before they make them with a budget.
SEM and paid search
Campaign structure, PPC strategy and optimisation, taught so that targets are reasoned from the business rather than lifted from a benchmark table.
SEO and AI-assisted content
Search strategy as it stands now, including answer- and AI-driven search surfaces, and content workflows that use AI as an instrument rather than a replacement.
AI personalisation and consumer behaviour
Where personalisation creates value and where it erodes trust, the subject of my doctoral research, taught with the uncertainty left in.
Curriculum design
Designing programmes, not just delivering them.
Beyond lecturing I design the programmes themselves: module architecture, assessment that mirrors real work, the sequence in which ideas have to arrive, and the revision cycle that keeps a curriculum from ageing badly in a field that moves this fast.
That has meant architecting a programmatic advertising curriculum from nothing, including the simulation tools it needed; building a professional certificate programme and rebuilding it twice as AI and automation changed what a marketer has to be able to do; aligning course content with industry partners and live case studies; and supervising Bachelor’s and Master’s students through campaign planning, KPI definition, experiment design and analytics.
Details of the certificate programme and the teaching tools built for it are on the Work page.
Research
Personalisation, trust, and the difference between people and patterns.
My doctoral work at Universität Klagenfurt examines how AI-driven personalisation shapes consumer trust and decision-making, using mixed-methods and experimental approaches.
The question underneath it is a practical one. Personalisation is usually evaluated on whether it lifts conversion, which is a short-horizon measure of a long-horizon relationship. A system can raise this quarter’s numbers while spending trust it did not earn and cannot see itself losing. I am interested in where that line sits, whether it can be measured before the damage shows up in revenue, and what a responsible personalisation system would have to do differently.
It is the same instinct as the rest of the work: the reported number is honest, and it is answering a smaller question than the one that matters.
Availability
Guest sessions, workshops and programme design.
I take on guest lectures, executive workshops, and curriculum or programme design work, in English, in Berlin or remotely.