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Applied Research

Product and UX research that turns broad product questions into sustained research programs, decision frameworks, and clearer roadmaps.

In industry, much of my work sits upstream of feature design: shaping the questions a team should answer, building the research capability to answer them, and turning broad product areas into coherent research programs. I combine qualitative research, surveys, behavioral and product data, and analytics to develop models and decision frameworks that inform product strategy and roadmaps.

This is not a public portfolio of case studies. Detailed process decks live in interview settings. Publicly, I focus on the kinds of research programs I build, the decisions they support, and the evidence structures they leave behind.

How I work

Shape the research agenda I often enter before the work has been reduced to a single study request. I help define what the team needs to learn, which decisions the evidence should support, what can be answered now, and how the research should sequence over time.
Build the capability around the work When the research system itself is missing, I build it: intake and prioritization, standards and templates, repositories, recurring research forums, roadmap practices, and the relationships needed to bring customer evidence into product development.
Combine methods around the decision I use qualitative interviews, ethnography and contextual inquiry, usability and concept testing, surveys, behavioral and product data, analytics, and measurement depending on what the decision requires. The method follows the evidence problem rather than the other way around.
Leave something reusable I look for outputs that can keep doing work after a study ends: behavioral models, personas, prioritization frameworks, measurement systems, research roadmaps, and decision frameworks that help teams reason across more than one release.

Selected areas of applied research

Foundational customer models and personas I use mixed methods to understand how people make decisions across a broader journey, then translate that evidence into shared models teams can use for strategy, prioritization, and design. My work has included interview-led persona research strengthened with survey evidence and behavioral segmentation.
Search, discovery, and content strategy I study how people search, compare, filter, interpret, and move from research into action. This has included job-search relevance, vehicle research and comparison, information architecture, educational content, terminology, and the relationship between human usefulness and machine discoverability.
High-consideration decisions I study the points where customers need enough confidence to keep moving through consequential decisions: evaluating offers, sharing information, comparing options, judging value, understanding next steps, and deciding what evidence is sufficient to act. Automotive retail and employment marketplaces have both been major settings for this work.
Early product concepts and decision risk I help teams test whether a product idea fits the customer's actual situation before build commitments harden. That includes foundational discovery, concept evaluation, interaction-model testing, and identifying when a proposed solution solves the wrong problem or creates new friction.
AI-assisted and generated product experiences My AI work is product-focused and deliberately narrow: evaluating how people interpret AI-generated or AI-assisted content, what evidence they need, where generated output creates uncertainty, and how those experiences fit into an existing decision journey. This has included automotive shopping and vehicle-content contexts.
Measurement and research operating systems I build the infrastructure that makes research cumulative rather than episodic, including recurring measurement, benchmarking, intake and prioritization, repositories, reusable reporting, and research roadmaps. The goal is to make evidence easier to retrieve, compare, and use across teams over time.

My industry experience spans automotive retail, employment marketplaces, enterprise sales tools, analytics, search and discovery, and early product development. For detailed methods, process, and case-study material, get in touch →