Using Research to Determine Unique Value Proposition
Summary
A story about how to quantify and use survey data to create audience clusters that are statistically representative of the people that use your online product or service. Edgar joins the dots between multiple research/pattern finding/storytelling techniques, such as proto-personas, affinity mapping, survey creation, quantification of qualitative data, organic clustering of audiences, user interviews, journey maps, and business modeling canvas. It makes research tangible and actionable: instead of being an end-point that provides stakeholders with insights, it takes stakeholders through an inclusive and structured process they can be part of.
Key Insights
-
•
Research often fails when stakeholders are not involved or don't trust the data sources and methodologies.
-
•
Treating research as a product, with stakeholders as users, drastically increases engagement and usability.
-
•
Using proto-persona workshops with cross-department stakeholders helps generate unbiased, relevant survey questions.
-
•
Clustering survey data via Python and correlation matrices can reveal meaningful user segments with statistical significance.
-
•
Statistical validity (e.g., 95% confidence at 5% margin) is critical for stakeholder buy-in in large user bases.
-
•
Behavioral and demographic clusters need to be augmented with emotional attributes to create actionable personas.
-
•
Affinity mapping large qualitative datasets reduces noise and distills coherent narratives and pain points.
-
•
Mapping pain points to measurable hypotheses enables prioritization based on user impact and implementation effort.
-
•
Divergent and convergent workshops using tools like the business model canvas help explore and refine value proposition delivery.
-
•
Iterative, lean research with frequent stakeholder feedback helps identify and minimize bias effectively.
Notable Quotes
"Research should be done the same way products are built, with stakeholders as your users."
"If you frame the research in terms your stakeholders understand, they will become research-hungry."
"We don’t make big deliverables because they create friction; instead, we create shared understanding through conversations."
"Proto-persona sessions helped us avoid departmental bias and uncover the questions stakeholders really cared about."
"We used a 0.8 correlation threshold to tightly cluster similar survey responses, balancing cluster count and inclusion."
"Clusters alone aren’t personas; we turned clusters into interview screeners and then emotional personas."
"We wrote hypotheses as we believe this pain point matters, here’s how we test it, and how success looks."
"Different stakeholders tackle the delivery problem differently, which gave us necessary divergent thinking."
"Biases surface as you iterate, so lean approaches help you find and fix them quicker."
"Marital status mattered because some people buy cars for their spouses or kids, not just themselves."
Or choose a question:
More Videos
"Respect, trust, and alignment helped us feel empowered and comfortable talking about anything."
Ruzanna RozmanGetting in Flow with Your Team
January 8, 2024
"We’re piloting surveys that ask customers how honest, simple, or reliable their experience was, then turn that into a score."
Sarah WilliamsA Framework for CX Transformation
June 11, 2021
"The foundation to getting good insights is system zero – the realistic, natural environment."
Jeff Ephraim Bander Ariane Rahn Philipp ReiterEye Tracking Gamechanger: Why Smartphone Eye Tracking will Revolutionize Your UX Research
March 11, 2022
"People saw small changes as having very large impact; a half-percent increase in conversion could mean 12 million dollars in revenue."
Eniola OluwoleLessons From the DesignOps Journey of the World's Largest Travel Site
October 24, 2019
"Donuts are delicious, right? Nobody doesn’t like donuts."
Dave Hoffer Joanne WeaverUX Job Search AMA #2 with Joanne Weaver and Dave Hoffer
May 21, 2025
"Organizational cracks and rickety bridges between teams are signals that design ops is needed here."
John CalhounHave we Reached Our Peak? Spotting the Next Mountain For DesignOps to Climb
October 1, 2021
"Being open and flexible to what's most helpful for the team at that moment is key."
Janelle EstesUX Research Trends
January 28, 2021
"Using AI to scan large archives of research is a game changer for meta-analyses, even if it’s imperfect."
Laura KleinHuman vs. machine: Testing AI’s ability to synthesize and analyze research
March 11, 2026
"Hubris is that belief the market will wait for your big bang release—executives have lost jobs over this."
Meaghan Waters Fotina KoutropoulousLack of Product Thinking will Doom Your Legacy Modernization
June 9, 2021
