Focus
Focus
I work at the intersection of analytics, customer understanding, and business decision-making. The recurring challenge is not producing more analysis. It is creating reliable decision support that people can use consistently across teams, products, and markets.
Three areas define most of that work.
Decision Intelligence & Business Decision Support
Decision Intelligence starts with the decision.
Before choosing a metric, analysis, model, or experiment, I want to understand what needs to be decided, who owns the decision, which actions are available, what evidence could materially change the choice, and when the decision needs to be made. That determines the appropriate analytical depth and prevents reporting from becoming an end in itself.
This matters when a business needs to explain a change in performance, choose between competing actions, evaluate an intervention, prioritize analytical work, or determine whether the available evidence is strong enough to act. I distinguish between descriptive and causal evidence, and between expected impact before a decision and measured outcomes afterward.
That perspective comes from leading analytics across customer, product, marketing, commercial, and operational decisions, and from introducing a decision-based approach that reframes reporting requests around business questions, decisions, expected outcomes, and measurable impact.
Customer Intelligence & Digital Growth
Customer behavior becomes valuable when it is interpreted in business context.
I look at journeys, funnels, customer segments, product and feature behavior, platforms, market differences, and commercial outcomes together. The questions are practical: where behavior changes, where customers encounter friction, how different groups behave, how product experiences affect conversion, and whether a pattern is specific to one market or holds more broadly.
Working across web and app environments and across many countries has made me particularly cautious about aggregated averages. Different markets, customer groups, and platforms can produce materially different patterns, and those differences can change the business interpretation.
My experience includes directing analysis of customer behavior, digital journeys, conversion funnels, audience segments, and product and feature performance across web and app platforms in international, multi-market environments.
Analytics Transformation & Operating Models
Replacing an analytics platform can be necessary. It is not transformation by itself.
A sustainable analytics capability also depends on priorities, measurement foundations, governance, roles and responsibilities, analytical standards, self-service, adoption, and the way analytics connects with the rest of the organization.
The problems I have worked on include fragmented reporting, inconsistent measurement and KPI definitions, unclear ways of working, limited self-service, and analytics technology that needs to become part of everyday decision-making rather than remain a specialist tool.
My experience spans both the technology and organizational sides of that work: measurement strategy, KPI standards, governance, platform modernization, self-service, implementation, training, and adoption. I have led major changes to analytics technology and measurement across web and app, while also defining the operating mechanisms required to make those capabilities usable and sustainable.
The objective is not to complete a migration. It is to leave the organization with a more consistent, trusted, and usable analytics capability.
Leadership and Organizational Scale
Across all three areas, the work is organizational.
I have built and developed international analytics teams, led both direct and matrix ways of working, and defined roles, priorities, standards, and stakeholder interfaces. The work has required close collaboration with Product, Marketing, CRM, UX, Commercial, Technology, and local-market organizations.
The scale has included more than 25 country websites at zooplus and regional digital analytics across Europe, Russia, India, and Africa at Amway. But scale is only part of the job. Analytics becomes more useful when capability extends beyond the central team through clear standards, self-service, training, mentoring, and people across the organization who can work effectively with data.
Continue Exploring