UX Telemetry for Data-Driven Product Decisions
Program: Philips Innovation Program — AI & Emerging Experiences
Data
Design Research
Amplitude
Mobile App
Desktop Platform
Scalable Ecosystem
Workflow Integration
Problem
As a medical device company, Philips operates under strict regulatory, legal, and privacy constraints that limit access to user data and restrict experimentation in real clinical environments. Working inside hospitals means flows cannot be freely tested in production due to patient safety risks, and customer data cannot be directly inspected or replayed. As products scaled globally, teams lacked safe, compliant ways to understand real user behavior, validate design decisions, and reduce risk before shipping—slowing learning and increasing reliance on assumptions.
The Work
I led the creation of a compliant UX telemetry system that enabled safe learning without exposing sensitive data or risking patient safety. We defined standardized event taxonomies, governance models, and privacy-safe instrumentation processes, embedding telemetry into hypothesis-driven design. By connecting UX telemetry with research, dashboards, and decision rituals, teams could validate flows, detect friction, and measure outcomes without accessing personal or clinical data.
My role
I worked as Design Manager and program lead, owning the strategy, rollout, and adoption of UX telemetry across teams. I aligned design, product, engineering, legal, and privacy stakeholders; established standards and processes; introduced new roles such as Data Governors; and scaled capability through training, documentation, and shared dashboards. My focus was enabling trust, compliance, and repeatability at global scale.
Outcomes
3+ product teams fully instrumented with standardized, compliant tracking
30–50% reduction in rework caused by assumption-driven design decisions
Enabled safe validation of workflows without accessing patient or customer data
Embedded UX telemetry as a standard input in design briefs and product planning