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How to think about this tier: A sidekick partnership for teams that already run studies, where I help you sharpen your research, level up your analysis, and put AI to work without losing nuance.
Under the hood: For teams who already research, but know it could be sharper, faster, and easier to act on. You keep owning the studies. I come in as a research and AI partner to tighten your plans, upgrade your analysis, and turn your existing work into clearer, more strategic decisions. Clarity Builder is ideal for teams with PMs, designers, or a solo UXR who are already conducting interviews and tests but are drowning in notes, repeating work, or struggling to get stakeholders to act on the findings. I come in as a sidekick to guide you through a rigorous study to get the deep insights needed to make an impact.
Great for product squads that already run research with active roadmaps and want reliable insights for a few key bets per quarter, but are not ready for a full, ongoing retainer.
What you get:
Research input review memo: A short written review (2–4 pages or equivalent slides) of 1–3 recent studies the team has run, highlighting strengths, gaps, and specific recommendations for improving questions, sampling, methods, and storytelling.
Optimized assets pack: A tighter discussion guide or usability test script, a clearer screener or participant profile, and a cleaned-up, decision-focused research brief to help your team gain deeper insights and run more successful research.
Co-designed study plan: A concise plan (1–2 pages or a few slides) for one live study you’re running, including research questions, methods, sample criteria, and how AI will support analysis.
Mid-study feedback notes: Written or recorded feedback after early sessions (for example, after 2–3 participants), with specific suggestions on adjusting the guide, flows, or tasks to improve signal.
AI-assisted analysis deliverables: A workspace or document (Notion, FigJam, Miro, or similar) showing transcripts or notes processed with AI, initial AI-generated tags or clusters, and your edits, merges, and annotations so they see what “human in the loop” looks like.
How to think about this tier: A sidekick partnership for teams that already run studies, where I help you sharpen your research, level up your analysis, and put AI to work without losing nuance.
Under the hood: For teams who already research, but know it could be sharper, faster, and easier to act on. You keep owning the studies. I come in as a research and AI partner to tighten your plans, upgrade your analysis, and turn your existing work into clearer, more strategic decisions. Clarity Builder is ideal for teams with PMs, designers, or a solo UXR who are already conducting interviews and tests but are drowning in notes, repeating work, or struggling to get stakeholders to act on the findings. I come in as a sidekick to guide you through a rigorous study to get the deep insights needed to make an impact.
Great for product squads that already run research with active roadmaps and want reliable insights for a few key bets per quarter, but are not ready for a full, ongoing retainer.
What you get:
Research input review memo: A short written review (2–4 pages or equivalent slides) of 1–3 recent studies the team has run, highlighting strengths, gaps, and specific recommendations for improving questions, sampling, methods, and storytelling.
Optimized assets pack: A tighter discussion guide or usability test script, a clearer screener or participant profile, and a cleaned-up, decision-focused research brief to help your team gain deeper insights and run more successful research.
Co-designed study plan: A concise plan (1–2 pages or a few slides) for one live study you’re running, including research questions, methods, sample criteria, and how AI will support analysis.
Mid-study feedback notes: Written or recorded feedback after early sessions (for example, after 2–3 participants), with specific suggestions on adjusting the guide, flows, or tasks to improve signal.
AI-assisted analysis deliverables: A workspace or document (Notion, FigJam, Miro, or similar) showing transcripts or notes processed with AI, initial AI-generated tags or clusters, and your edits, merges, and annotations so they see what “human in the loop” looks like.