Behavioral telemetry and workflow analysis
Clickstream analysis, journey diagnosis, benchmarking, and behavioral pattern detection to show how product use actually unfolds in the field.
Quantitative User Experience Research
I help teams turn behavioral data into better product decisions.
I lead quantitative user experience research that combines behavioral research, statistics, experimentation, and product thinking. This portfolio highlights confidentiality-safe summaries of work spanning multi-step journeys, trust-sensitive decisions, segmentation systems, and workflow design.
About
Statistical depth when needed. Strategic breadth when it matters.
My work sits at the overlap of behavioral research, statistics, and product decision-making. I use quantitative UX research to help teams understand users, workflows, and product behavior well enough to make better decisions.
That means bringing statistical depth when the problem calls for analytics, predictive modeling, experimentation, or measurement rigor, and statistical breadth when the goal is customer insight, rapid feedback, or strategy impact.
What I optimize for
- Questions anchored to real product and business decisions
- Methods matched to uncertainty rather than habit
- Behavioral data combined with survey and workflow evidence
- Outputs that survive handoff into roadmap and design work
Personal
Grounded in service, shaped by curiosity, committed to human flourishing.
The way I work is shaped by service, stewardship, humility, and care for people. Those values are rooted in my Christian faith, but I try to express them in ways that are accessible in secular, scientific, and multidisciplinary settings.
Outside client work, I am a trail runner, a volunteer, and a longtime student of how humans learn, decide, adapt, and make meaning. My academic background includes doctoral work in HCI, adaptive interfaces, and user modeling, and I continue to be drawn to technology that helps people live and work with more clarity, dignity, and agency.
A Few Anchors
- PhD research in HCI, adaptive interfaces, and user modeling
- Trail runner with a bias toward endurance, discipline, and long horizons
- Volunteer-oriented and motivated by work that is useful beyond the dashboard
- Interested in technology that augments human judgment rather than replacing it
Selected engagements
Representative Research Engagements
A selection of anonymized engagements spanning product strategy, trust, conversion, segmentation, and adaptive experience design. Details are intentionally generalized to respect client confidentiality while showing the kinds of problems, methods, and outcomes I help teams navigate.
Toolkit
Methods I use for customer insight, rapid feedback, and strategy impact
Survey measurement and latent constructs
Survey design, scale development, preference measurement, validation work, and latent-construct modeling for questions that are not directly observable.
Segmentation, clustering, and classification
Segmentation systems grounded in observed behavior, profiling, classification, and measurable product implications rather than static archetypes.
Experimentation, prioritization, and predictive modeling
Experimental thinking, feature prioritization, predictive modeling, and decision-ready synthesis that help teams choose where to invest next.
Process
A repeatable path from ambiguity to evidence-backed action
Frame the decision
Clarify the business risk, the product question, and what would actually change if the team learned something new.
Choose the right level of statistical depth
Match the method to the problem, whether that means experimentation, telemetry analysis, survey measurement, segmentation, or a blended design.
Integrate behavior, measurement, and context
Bring together behavioral data, workflow signals, and well-structured research measures so patterns are interpretable rather than just descriptive.
Turn analysis into operating decisions
Translate findings into prioritization frameworks, scorecards, segment definitions, recommendations, and roadmap inputs that teams can actually use.