My career has never followed a straight line. It has followed a pattern.
At Mattel in Amsterdam and Standard Chartered in New York I was close to data before most marketing functions knew what to do with it. Sales dashboards, pricing analysis, anomaly detection. The tools were basic but the instinct was forming — data is only useful if it's structured to answer the right questions.
Edge Consultants in Oslo was where that instinct first found real expression. Working with Jotun marine paints, I helped redesign how a product was sold entirely. Sea Quantum X2000 was a premium anti-fouling paint that promised measurable efficiency over time — but nobody had ever built the infrastructure to prove it. We built an ocean liner efficiency calculator that tracked vessel performance against a moving baseline across global ocean biomes. For the first time in the marine segment, Jotun could sell a performance guarantee rather than a product. Their marine paints division achieved a CAGR of 10.2% over the following decade. The technology wasn't new. The thinking was.
At OMD Canada I arrived as the agency's first Marketing Scientist, embedded on McDonald's Canada. In my second week I sat in a digital performance meeting and watched $11.8 million being optimised toward website clicks for a brand whose customers don't research lunch online. The measurement was wrong and the wrong measurement was producing the wrong conclusions. I changed what we measured, introduced visibility as the optimisation goal, and doubled digital ROI quickly. When Meta offered us a beta test of their new Store Visits capability I was ready for it. Not because the technology was obvious but because I had already identified what we needed to measure. The result was a more than fivefold improvement in digital ROI over two years.
Klick Health brought me into pharmaceutical marketing in 2020. The industry was data rich and analytically conservative. Decile-based HCP segmentation ranked doctors by prescription volume but told you nothing about where they were heading. I had been looking at Netflix's machine learning recommendation algorithms and saw the same problem solved differently. We adapted the approach, trained a model on prescribing trajectory rather than volume, and built Klick's first machine learning product. It halted quarterly declines for Takeda's Trintellix and was subsequently sold to eight clients generating $2.2 million in billings. The algorithm wasn't new. The application was.
The taxonomy work, the first-party data strategy, the learning agenda frameworks — all of it has been a version of the same thing. Finding where the infrastructure doesn't match the ambition and building something that closes the gap.
That's what brought me to Nodal Strategy. The queried era is the largest version of that gap I've encountered in twenty years. Most brands have content built for human navigation in a world moving to conversational retrieval. The infrastructure doesn't match where attention is going. That's a problem I know how to solve.