Better data. Clearer thinking. Better decisions.
I help organisations improve their marketing data, investigate difficult questions and use the findings to make better decisions.
Sometimes the problem is technical: personal information is leaking into analytics, conversions are recorded incorrectly or important data is missing.
Sometimes the numbers are technically correct, but their interpretation is wrong. A customer definition has changed. Two reporting periods are no longer comparable. An apparent improvement reflects a change in measurement.
And sometimes the data is good enough, but nobody has asked a useful question.
My work starts by understanding which problem we need to solve.
The questions clients bring to me
- Can we trust our conversion figures?
- Why are we generating more leads but not more sales?
- What should we measure before launching a new digital service?
- Is our analytics collecting information it should not?
- Can AI use our data reliably, and what context does it need?
I help turn questions like these into focused investigations, practical improvements and recommendations. That can involve examining how data was collected, analysing customer behaviour, defining measurement requirements or challenging the assumptions behind a report.
I have investigated personal data leaks into GA4, helped organisations move to alternative analytics platforms and used unsupervised machine learning to develop customer segments.
Across these assignments, the essential task is the same: understand what the evidence supports and what to do next.
From historical sources to marketing data
My first career was in historical research. I later studied economics and moved into digital analytics.
Historical research taught me to question sources. Who produced this information? For what purpose? What is missing? Can two sources really be compared?
Those questions are equally useful when examining a CRM export or a marketing dashboard.
Economics added another perspective: incentives, trade-offs, quantitative methods and decisions under uncertainty.
Together with more than 15 years of practical analytics experience, this background shapes how I work. I examine both the calculations and the assumptions that make those calculations meaningful.
How I approach analytics
Start with a decision.
Before collecting more data or building another report, establish what someone needs to decide and how the evidence could help.
Improve the data that matters.
Define metrics clearly, investigate consequential errors and make limitations visible. Prioritise improvements according to their effect on the decisions you face.
Make uncertainty explicit.
A useful recommendation explains what we know, what we are assuming and what could change the conclusion.
Keep the system understandable.
Measurement should be proportionate to its purpose, respectful of privacy and maintainable by the people responsible for it.
My CARE framework brings these principles together: Collect → Analyse → Recommend → Experiment. Collection provides the foundation. Analysis, recommendations and experimentation turn it into something useful.
AI needs the same analytical discipline
AI can accelerate parts of analytical work. It can also produce a confident explanation without recognising that the underlying definitions changed last year.
I help organisations establish the data and business context needed for useful AI-assisted analysis. This can include warehouse requirements, shared metric definitions, documentation and workflows for assistants or agents.
The starting point is a concrete task. We then define how the result will be checked and where human judgment is needed.
How we can work together
I offer focused projects and fractional advisory engagements:
- Marketing Data Quality Assessment: establish what your data can support and which improvements matter.
- Digital Analytics Data Privacy Assessment: examine collection behaviour, data flows and technical privacy issues.
- Marketing Analytics Investigations: explore a business question and develop recommendations from the available evidence.
- Measurement Strategy & Design: define the metrics, sources and collection requirements your organisation needs.
- AI & Analytics Advisory: design the data foundations, context and evaluation needed for useful AI workflows.
- Fractional Analytics Advisor: bring experienced analytical judgment into your team on an agreed part-time basis.
Each engagement has a defined purpose, scope and initial term. I work directly with business leaders, marketers, analysts and technical teams.
My platform experience includes GA4, Piwik PRO and Matomo. The appropriate approach depends on the question, your existing systems and your organisation’s requirements.
A little more about me
I am based in Helsinki and work remotely in Finnish, English and German.
I co-founded Hopkins in 2016 and serve on its board. My experience includes work with B2B companies, healthcare providers, public sector organisations and international businesses.
I have also taught as a visiting lecturer at Aalto University and spoken at international conferences.
Outside consulting, I play competitive chess, study languages and continue to explore history and economics. Researching difficult questions and finding better explanations remain enduring interests.
What are you trying to understand?
You do not need to arrive with a technical specification.
Tell me which decision you face, which numbers you doubt or which question your current reports cannot answer. Then we can determine what kind of work would help.