Product Research · Example Report
Using Product Research to Decide What to Build
Product research can reveal what potential users actually want, develop and test product possibilities, and provide a stronger basis for deciding what should be built and prioritized.
Joel Vuolevi · September 7, 2026
From Product Idea to Product Direction
- A product idea does not automatically determine what the product should actually do.
- Potential users may reveal needs and possibilities beyond the original assumptions.
- Product research can explore those possibilities and provide a basis for deciding what to build.
The ThoughtTapestry Product Question
ThoughtTapestry began with a broad concept: a system for recording thoughts, ideas, observations, and questions over time and using AI to understand them together.
Many capabilities were plausible: organizing thoughts, finding connections, developing ideas, identifying gaps, generating next steps, bringing back forgotten thoughts, and more.
The Product Question
Which capabilities would potential users actually value, and what should ThoughtTapestry prioritize?
IntelAnvil investigated this through a staged research process with UK-based participants recruited through Prolific. The first study explored what potential users wanted without restricting them to a predetermined feature list. The second compared the resulting product possibilities to determine which capabilities users valued most.
1. Discover What Potential Users Want
The first study deliberately avoided presenting participants with a predetermined feature list.
In an initial study (n = 40), participants were given the underlying product premise and asked what they would want such a system to do.
Participant Question
Imagine that over the course of a year you had recorded hundreds of ideas, observations, questions, and thoughts about things you were interested in or working on. If a system could understand all of them together, what would you want it to do with that information?
What emerged
Percentages indicate the share of responses that explicitly mentioned each theme. One response could contribute to several themes.
The results showed that participants wanted more than conventional note organization. They also wanted the system to help them understand, develop, connect, and act on their accumulated thinking.
The responses were analyzed using Text Response Hub, an AI-assisted qualitative analysis system developed by IntelAnvil.
2. Turn the Findings Into Product Possibilities
Research does not mean simply building the features mentioned most often.
IntelAnvil combined recurring participant needs, promising ideas from individual responses, and independent product hypotheses into a set of candidate capabilities for further testing.
| Capability | Popularparticipant demand | Interestingindividual ideas | Independentproduct thinking |
|---|---|---|---|
| Organize my thinking | ●●● | ● | ● |
| Show me the big picture | ●●● | ●● | ●●● |
| Discover connections I missed | ●●● | ●●● | ●●● |
| Bring back relevant forgotten thoughts | ●● | ●●● | ●●● |
| Show how my thinking has evolved | ● | ●●● | ●● |
| Develop my ideas further | ●●● | ●●● | ●●● |
| Generate new ideas from my existing thinking | ● | ●●● | ●● |
| Find the ideas most worth pursuing | ●●● | ●●● | ●● |
| Turn my thinking into next steps | ●●● | ●●● | ●● |
| Find gaps in my thinking | — | ● | ●●● |
| Find contradictions in my thinking | — | — | ●●● |
| Challenge my assumptions | — | — | ●●● |
The indicators show why each capability entered the next stage. They are qualitative provenance indicators, not participant ratings.
Human product judgment was used to determine which ideas represented meaningfully different capabilities worth testing.
3. Test What People Value Most
In a prioritization study (n = 36), participants repeatedly chose which of two capabilities they would personally find more valuable, forcing tradeoffs between competing product possibilities.
Capability preference
Relative preference strength reconstructed from participants' pairwise choices between competing product capabilities.
The strongest preference was not for organizing notes, but for turning accumulated thinking into practical next steps. Several other highly ranked capabilities also went beyond conventional note management: developing ideas, identifying which ideas are worth pursuing, and generating new ideas from existing thinking.
Percentages are relative preference-strength estimates reconstructed from participants' pairwise choices, rather than the percentage of participants selecting each capability.
What the Research Changed
The research provided a stronger basis for deciding:
- Which capabilities deserve greater emphasis
- Which ideas should remain secondary
- Where ThoughtTapestry differs from conventional note-taking products
- What should be developed and tested next
The research provided a stronger basis for deciding what ThoughtTapestry should build and prioritize next.
From Product Idea to Market Evidence
A product can be investigated progressively: first determine what it should do, then evaluate whether the resulting opportunity is worth pursuing, and finally test how potential customers respond to a real proposition.
Stage 1
Current Report
Product Research
What should the product do? Explore what potential users want and determine which capabilities deserve priority.
Stage 2
Market Research
Is the product opportunity worth pursuing? Test customer interest, perceived value, and willingness to pay.
View Market Research →Stage 3
Website-Led Market Research
How do potential customers respond to the real proposition? Put the proposition in front of potential customers and test how they understand it and how interested they are.
View Website-Led Market Research →Have a Product or Product Idea to Test?
IntelAnvil can investigate what potential users want, compare possible capabilities, concepts, and directions, and provide a stronger basis for deciding what to build or prioritize.