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01

Discover

Before I talk with users, launch a survey or usability study, I spend time figuring out what questions are worth asking. The research questions shape everything downstream, so I work with stakeholders to understand what we need to learn. From there we can start thinking about participant demographics and planning the study.

02

Plan

After meeting with stakeholders and identifying participant demographics, I select research methods based on the discussions I had with stakeholders. Sometimes that means moderated interviews, unmoderated usability testing, card sorting or a it could mean something else, like a survey. Regardless of the chosen research methodologies, the methods always follow the business needs and research questions.

03

Research

I conduct research: qualitative, quantitative or both (mixed methods). Some of the research methodlogies I use regularly include participant interviews, usability testing, surveys and focus groups. I listen carefully to what people say but also pay close attention to what they actually do. Those two things are often very different, and the gap between them is usually where we can identify the most useful insights.

04

Analyse

I go through everything I heard and observed and look for patterns that repeat across participants. Individual stories are interesting but patterns that repeat across sessions is most meaningful.

05

Recommend

I write recommendations that are direct, specific, and grounded in evidence. My goal is to produce a document for the people who have to make business or design decisions and who need to know exactly what the research says, what it means, and how the information can help them in their work.

01

Lead the Research

Before any AI touches the data, I design and run the study myself. That hands-on involvement makes my review of the AI output meaningful. I can only catch what the AI gets wrong if I was the one in the room.

02

Capture and Structure

I clean and label the transcripts, organise my notes, and structure everything before it goes near an AI. Poorly structured input produces poorly structured output. The AI has no way of knowing the difference. I do.

03

AI-Assisted Synthesis

I use AI to surface patterns and cluster themes across sessions. It processes transcripts faster than I can. But it cannot tell me which patterns matter and which are noise. That judgment stays with me.

04

Validate and Refine

I test every theme the AI surfaces against the raw data. Some hold up. Some need to be merged or reframed. Some get cut entirely. This is where the actual insight gets made.

05

Build and Disseminate

I turn the refined findings into something other teams can actually use. At Canada Post, I built a feedback template for a development team with no prior research experience. AI made it faster. I made sure it was worth using.

A clear process produces clear results.

Replace with a description of the research brief
1 Discover
Replace with a description of the research plan
2 Plan
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3 Research
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4 Analyse
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5 Recommend
Let's talk
Get in touch
Replace with a description of the research materials
1 Lead the Research
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2 Capture and Structure
Replace with a description of the AI output
3 AI-Assisted Synthesis
Replace with a description of the validated insights
4 Validate and Refine
Replace with a description of the final deliverable
5 Build and Disseminate
Let's talk
Get in touch

Let's talk

Have a project in mind? Drop me a note.