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
"Each organization's design ops team looks a little different, but the foundations are the same."
Jilanna WilsonDistributed DesignOps Management
February 26, 2019
"Marketplace partners have to demonstrably save people money, aligning with Propel’s mission."
Alan Williams Rose DeebDesigning essential financial services for those in need
February 10, 2022
"Matchmaking connects AI capabilities to user needs so you find the low hanging fruit projects."
Dan SafferWhy AI projects fail (and what we can do about it)
May 14, 2025
"Testing AI products requires longitudinal methods to see how relationships and experiences evolve."
Jonathan Fairman Kevin JohnsonIntegrating generative AI into enterprise products: A case study from dscout
June 5, 2024
"We need to democratize insights, not just democratize research."
Jemma Ahmed Subhasree Chatterjee Robert Fabricant Alexandra Jayeun Lee Ben RobinsCollaboration: learning from other fields beyond our own [Advancing Research Community Workshop Series]
August 7, 2024
"Failure isn’t discouraging; it’s an opportunity to learn and improve your approach."
Kim Fellman CohenMeasuring the Designer Experience
October 23, 2019
"No bee micromanages another; they have different roles and contribute independently but in sync."
Mariesa LenzWhat Beekeeping Taught me about Product Teams
October 29, 2025
"Full automation of research is simply not working."
Daniel Korczynski Justyna ParmeeFrom generic to contextual research insights with AI | Live Q&A
March 11, 2026
"The first impression is crucial as it triggers excessive unconscious processes that influence preferences."
Daniela Magaña Flores Ariane Rahn Jeff Ephraim BanderAhead of Competition: Learn What UX Benchmarking Can Do for Your Business Today
March 10, 2022
