I turn customer, campaign and journey data into clear evidence for where to invest, what to improve and what is actually driving growth.
Incrementality, holdouts and mix modelling that separate real lift from last-click credit.
Experimentation programs with the power, and the culture, to ship tests before opinions.
Journey analytics across web and app that surface the drop-offs costing real money.
Foundations, governance and mentoring that turn one analyst's work into a lasting capability.
Client names are withheld – these are anonymised versions of engagements delivered in prior in-house roles. Each case is the same: a real problem, a rigorous method and a clear business outcome.
Platform-reported conversions told finance a story the real data didn't support.
Decisions ran on opinion and HiPPOs. Nothing was being proven before it shipped.
Measurement was about to break as third-party cookies went away across five brands.
Every new customer was treated as equal, so bidding chased volume over worth.
If a number can't survive a holdout or control, it's not a result. It's just a story.
Every analysis ends with a decision. A chart that changes nothing is a cost.
Measurement should reconcile with revenue. One defensible truth, not two.
Multi-touch attribution feels rigorous and isn't. What it's actually measuring, and what to use instead.
A plain-language tour of holdouts, geo tests and the traps that make a "lift" disappear under scrutiny.
Prioritisation, power, and the cultural work of getting an org to ship the test before the opinion.
Why marketing and finance disagree on the same number, and the reconciliation that buys back trust.
A journey classifier, a holdout calculator and a box-office forecasting model backtested at 87% accuracy – every forecast published before the result, scored after. The public proof of everything on this page.
I'm a marketing analytics and measurement lead who's spent 14 years turning marketing and customer data into decisions people can defend in a boardroom.
I work across web, app and campaign measurement, with deep ownership of the Adobe stack and GA4, and a focus on the harder end of the discipline: incrementality, experimentation and mix modelling. Across financial services, retail and telco, what I care most about is the moment a number turns into a budget decision – and I build AI-native workflows to get there faster. Outside client work I publish essays on measurement, run StoryPrism, and argue over whether dashboards are actually useful.
If you're hiring, facing attribution risk, or building a test program from scratch, let's talk.
