SenseKit: research data collection instruments
Three interactive research tools that turn subjective perceptions into structured, visualized data, in real time, with zero setup for participants
Case study
SenseKit: research data collection instruments
Links
The Challenge
UX researchers, strategists, and facilitators run perception-based exercises in workshops, interviews, and surveys, but lack digital tools that match the specificity of their methods. Generic survey tools can't represent 2D positioning, bipolar scales with standard deviation indicators, or aggregate dispersion analysis. This forces researchers to either simplify their methods (losing richness) or manual-process results (losing time).
Research methods like stakeholder mapping, semantic differentials, and competitive positioning are powerful, but the tools available to run them are embarrassingly outdated. Researchers typically resort to Google Forms (flat, no visualization), Miro (collaborative but unstructured), or pen and paper (functional but unscalable). None of these give you real-time aggregated visualization of participant responses.
SenseKit is a suite of three purpose-built instruments: StakeMap for collaborative stakeholder positioning, SemDiff for semantic differential scales, and CompScape for competitive landscape mapping. Each is a standalone web app with a shared design system, live at sensekit.eu.
"Researchers need tools that match their methodology, not the other way around. A stakeholder mapping exercise should let participants position items on a 2D matrix, not rank them in a list. A semantic differential should show mean profiles across participants, not just individual responses. Existing tools force researchers to approximate their methods rather than implement them faithfully."
The gap between research methodology and available tooling means insights arrive late, visualizations are inconsistent, and researchers spend more time on logistics than analysis. Worse, simplified tools produce simplified data, losing the nuance that makes perception-based methods valuable.
Researchers build makeshift tools: Google Slides with draggable shapes, Miro boards with color-coded sticky notes, Excel charts assembled manually from survey data. Each project reinvents the same infrastructure. Results are aggregated by hand, often days after collection, when the workshop energy is long gone.
Research
Method-Tool Gap Analysis
Methods Require Spatial Input
All three methods involve positioning items in space: on axes, on scales, on matrices. Survey tools that reduce this to dropdowns or sliders lose the spatial relationship that makes the method meaningful.
Aggregation Is the Value
Individual responses are interesting; aggregated patterns are actionable. Showing where participants agree (tight clusters) and disagree (wide dispersions) is where insight lives. No existing tool provides this in real time.
2-4 hours post-processing per exercise
Manual aggregation of a 10-participant stakeholder mapping takes 2-4 hours. With SenseKit, it's instant and continuous.
Participant Experience Research
Zero-Friction Entry Is Essential
Participants in workshops have seconds of attention, not minutes. Any login, download, or setup kills engagement. The ideal tool is a link that opens directly to the exercise.
Spatial Interaction Feels Natural
Drag-and-drop positioning on a matrix is intuitive in ways that form fields are not. Participants understand 'place this where you think it belongs' immediately.
"I want to share a link and have people doing the exercise within 5 seconds."
— Personal design requirement
Key Insights
Each method deserves a purpose-built instrument
Stakeholder maps, semantic differentials, and competitive landscapes are different methods with different data structures. Forcing them into a generic tool sacrifices what makes each method uniquely valuable.
Real-time aggregation is the killer feature
Seeing results update live as participants respond transforms data collection from a passive process into an engaging, discussion-generating experience.
Statistical indicators surface consensus and conflict
Averages alone are misleading. Standard deviation indicators (SemDiff) and dispersion ellipses (CompScape) show not just where the group lands, but how much they agree, which is often more interesting than the position itself.
Participants should think about the question, not the tool
No accounts, no tutorials, no onboarding. Open the link, see the exercise, interact immediately. The tool should be transparent: invisible infrastructure for the method.
Shared infrastructure, distinct experiences
The three tools share a design system, auth pattern, and data architecture, but each has a UI shaped entirely by its method. Consistency in plumbing, specificity in interaction.
Goals & Principles
StakeMap: Collaborative 2D positioning with aggregation
Participants drag stakeholders onto a customizable 2D matrix. The researcher sees averaged positions and dispersion clouds across all participants in real time.
SemDiff: Semantic differential scales with statistical depth
Participants rate items on bipolar scales (e.g., Innovative–Traditional). The dashboard shows mean profiles with standard deviation bars, enabling comparison across participants and items.
CompScape: Competitive landscape with consensus mapping
Participants position competitors on a 2D matrix. Dispersion ellipses reveal where participants agree and where perceptions diverge, surfacing contested positioning.
Shared: Frictionless participant experience
Anonymous access via link. No login for participants. Firebase anonymous auth handles state. Project creation and analytics require researcher authentication.
Guiding Principles
Method fidelity over feature count
Each tool does one method well rather than approximating many. The constraints of the research method define the feature set.
Aggregation is continuous, not post-hoc
Results update in real time as participants respond. The researcher never waits for 'processing': insight emerges during collection.
Export is a first-class feature
Research data must leave the tool. CSV export, structured data, and visual exports ensure SenseKit feeds into whatever analysis pipeline the researcher uses.
Solution Design
Monorepo with Shared UI Library
Three tools that need visual consistency and shared infrastructure, but each has distinct interaction patterns and data models.
pnpm workspaces monorepo with a shared-ui package containing all base components (buttons, cards, modals, layout) built on Radix UI and Tailwind. Each app has its own Vite configuration, Firebase project, and domain (stakemap.sensekit.eu, etc.).
Each research method has fundamentally different data structures (2D coordinates vs. scale values vs. competitive positions), but the researcher-facing dashboard patterns (project management, export, settings) are identical. The monorepo lets each tool diverge where it needs to while sharing 80% of the UI infrastructure.
Real-Time Aggregation with Firebase Realtime Database
Participants respond asynchronously during workshops. The researcher needs to see aggregated results update live: not after a page refresh, not after export, but continuously.
Firebase Realtime Database with listener-based subscriptions. When a participant submits a position, the researcher's dashboard updates within milliseconds. Aggregation (means, standard deviations, dispersion ellipses) is computed client-side from the live data stream.
Firebase's subscription model means real-time aggregation 'just works': no polling, no custom WebSocket infrastructure. Client-side computation keeps the server stateless. Anonymous auth for participants means no login friction. The tradeoff (Firebase vendor lock-in) is acceptable for the reliability and speed it provides.
Dispersion Ellipses for Consensus Visualization
In competitive positioning and stakeholder mapping, the average position tells you where the group center is, but it doesn't tell you if everyone agrees or if the average masks a split opinion.
Implemented dispersion ellipses calculated from standard deviation in both axes. Tight ellipses mean consensus; wide ellipses mean contested perception. Combined with individual participant dots and averaged center points for complete picture.
The dispersion ellipse is the key innovation. In a competitive analysis, seeing that 'Competitor A' has a tight ellipse (everyone agrees on its position) while 'Competitor B' has a wide ellipse (contested perception) is often more strategically valuable than the positions themselves. It surfaces the quality of consensus, not just its direction.
Outcomes & Impact
3 purpose-built research instruments, each live on its own domain
Real-time aggregation: <100ms from participant response to researcher dashboard update
Zero-friction participation: no login, no download, immediate access via link
Shared UI library: 80%+ component reuse across three distinct applications
Post-processing time reduced from 2-4 hours to zero (aggregation is instant and continuous)
Research methods are implemented faithfully: spatial input for spatial methods, not flattened into forms
Dispersion visualization surfaces consensus and conflict that averages alone would hide
Researchers can react to incoming data during workshops instead of processing afterward
The shared design system ensures professional, consistent experience across all three tools
CSV export preserves all raw data for downstream analysis in R, Python, or Excel
Reflections
What Worked
Method-Specific Design Prevented Feature Creep
By defining each tool as an implementation of a specific research method, the scope was naturally constrained. The method defined the features, not the other way around.
Real-Time Aggregation Changed Workshop Dynamics
Facilitators could project the dashboard during exercises, using live results as discussion prompts. Data collection and sense-making happened simultaneously rather than sequentially.
Monorepo Paid for Itself Quickly
The upfront investment in shared-ui meant the second and third tools were dramatically faster to build. CompScape was built in a fraction of the time of StakeMap because the infrastructure was already there.
Challenges
Statistical Visualization Requires Careful Defaults
Dispersion ellipses, standard deviation bars, and aggregation methods all require design decisions that have statistical implications. Getting the defaults right (e.g., when to show ellipses vs. individual dots) required balancing accuracy with accessibility.
Three Apps Means Three Deployment Pipelines
Each tool has its own Vercel project, domain, and Firebase instance. Coordinating updates across the suite required more ops work than a single application.
Key Learnings
Purpose-built tools outperform generic ones when the method has specific data structures: a stakeholder map isn't a survey, and it shouldn't feel like one
Real-time data changes the research dynamic: seeing patterns emerge live creates energy and discussion that post-hoc analysis never recaptures
Building research tools teaches you about research methods at a deeper level: implementing a semantic differential forced me to understand the statistics behind it
Shared infrastructure with distinct experiences is the right pattern for tool suites: consistency in plumbing, specificity in interaction
The best tools disappear: participants should think about the question, not the software