Research tools should
earn trust.
We built QuestionPunk for researchers who need methods they can inspect, reproduce, and defend — not a black-box tool that spits out a chart.
Built by a researcher, for researchers.
Jake has spent a career in journalism, data analysis, and data engineering. Across every role, the same problem kept coming back: teams needed better tools to get honest answers and reproducible evidence — and the tools never quite existed.
QuestionPunk is that tool. One workflow for survey design, adaptive interviews, and analysis — with transparent AI setup that researchers can inspect and report on, not just trust.
If results matter, methodology matters. I wanted a tool that helps teams move faster without hiding how the answers were reached.
Three problems we set out to solve.
Fragmented workflows
Research used to mean stitching together separate tools for design, recruitment, and analysis. That split loses signal.
one tool that covers design, recruitment, and analysis end-to-end — no stitching, no context lost in handoffs.
Static questionnaires
Classic surveys miss the follow-up questions that only reveal themselves once a respondent starts talking.
an AI that probes unclear answers while the respondent is still warm — the follow-ups happen in the moment, not in synthesis.
Manual synthesis
Teams spend days cleaning, coding, and summarising transcripts before they can make a call. That’s time the decision doesn’t have.
reports that ship alongside the raw responses — themes, sentiment, and an executive summary are ready the moment the study closes.
Four principles that guide every decision.
Researchers first
Our roadmap is driven by researchers and the experiments they need to run — not by growth-hack pressure.
Full transparency
Prompts, model choices, and branching logic are visible so studies can be documented, reviewed, and reproduced.
No-code control
Adjust prompts, models, and study setup without filing a ticket with engineering.
Practical affordability
Academic and lean teams should be able to evaluate modern methods without enterprise-tier pricing.
What we’ve built so far.
Guided by researchers who use the product daily.
Travis Tae Oh, Ph.D.
Marketing Professor, Yeshiva University
Travis is a marketing professor at Yeshiva University with published research on generative AI in academia. He has been embedded in our development process from the start, providing rigorous feedback that has directly shaped how QuestionPunk works.
A 1,000-survey Qualtrics veteran, Travis now runs his research on QuestionPunk.
Read his research on GenAI for marketing insightQuestions, feedback, or just want to talk research?
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