How I Think About Research

Good research does more than tell a team what users said.

It explains why people behave the way they do, where an experience breaks down, and what the product should do differently because of it.

My work often begins with an ambiguous question — why players are leaving, what makes an experience worth returning to, where customers lose confidence, or whether a new product idea deserves investment.

From there, I build the research approach around the problem rather than forcing the problem into a favorite method.

What I Bring to a Team

Research Craft

I combine generative and evaluative research to understand both the problem and the experience being built to solve it.

Depending on the question, that can mean interviews, usability testing, surveys, journey mapping, ethnographic research, benchmarking, experimentation, or behavioral analytics.

The goal is not simply to run a study. It is to understand what is happening, why it is happening, and what deserves action.

Product Impact

I care just as much about what happens after the research.

Some of my strongest work has started with a research finding and ended with a shipped feature, a changed roadmap, a new experiment, or a different way for a team to think about its users.

I work closely with Product, Design, Engineering, Analytics, Marketing, and leadership, bringing research into the decision-making process rather than delivering findings only at the end.

AI-Augmented Research

I use AI throughout the research workflow to help me work faster across large and complex sets of information — while keeping human judgment and source validation at the center.

I use AI to accelerate thematic coding, open-text analysis, synthesis, pattern detection, and reporting, helping me move from raw research data to meaningful signals more efficiently.

I also use AI to support competitive and market research, synthesizing competitor experiences, product patterns, market signals, and user evidence to better understand the broader opportunity around a product.

For me, AI is not a replacement for research judgment. It creates more room for it.

AI helps me move through information faster. Research rigor determines what I trust.

How I Like to Work

Find the signal in complex problems.
I’m comfortable starting with ambiguity, separating assumptions from evidence, and finding the research question underneath the business question.

Connect the qualitative and quantitative.
Qualitative research helps me understand why something is happening. Quantitative evidence helps me understand how broadly it matters.

Push research beyond the report.
A finding becomes valuable when it changes a decision, an experience, an experiment, or the way a team understands its users.

Work as a partner.
I prefer research that happens alongside the team — shaping the question, evaluating the evidence, and deciding what to do next together.

Research Toolkit

Generative Research · Evaluative Research · Mixed-Methods Research · Survey Design · Usability Testing · User & Player Interviews · Journey Mapping · Jobs to Be Done · Ethnographic Research · Benchmarking · Behavioral Analytics · Experimentation · Research Strategy · AI-Assisted Synthesis · Competitive & Market Research