Project background
This crisis has shifted the conversation toward Environmental Health, as research proves our homes act as an "external nervous system." The colors, textures, and spatial layouts we live with directly impact our cortisol levels and mood. For the millions of people now spending the majority of their day indoors — remote workers, students — a visually "loud" or poorly arranged home can lead to chronic sensory fatigue.
The Problem
Users intuitively sense when a space feels "off" but lack the design literacy to diagnose why. With professional help inaccessible, many turn to superficial social media trends that offer quick fixes but fail to improve their well-being. There is a clear need for accessible, low-pressure tools that teach the principles of restorative design.
The Idea
Rooted Academy — a photo-based room audit, bite-sized design lessons, and optional non-commercial product suggestions. That shape came from the brief; whether it would actually earn people's trust is what research was for.
Why I chose this brief
My project utilizes the home as a fundamental and universal mental health tool. Synthesizing my background in architecture and human-centered experience, as well as my deep interest in psychology, I aim to leverage UX/UI design to make restorative design principles accessible to a broad audience, empowering users to modify their living spaces to better align with their sensory requirements.
Starting goals
User Goal
Help someone identify what's stressing them about their space and build design literacy to stop guessing.
Business Goal
Establish Rooted Academy as a trusted home-wellness mentor, earning revenue through ethical, contextual suggestions — not a hard sell.
Approach
Iterative, not linear — every phase fed back into the one before it: Research (interviews, SWOT, affinity mapping, personas) → Define (HMWs, roadmap, sitemap, flows) → Ideation (wireframes + mid-fi testing) → Branding (visual identity, logo, UI kit) → Design (hi-fi mockups) → Test (usability testing) → Iteration (refinement + feedback survey).
Research
Interviews
Six one-on-one, semi-structured interviews, remote via Google Meet, transcribed with Gemini. Mixed housing — renters, a homeowner, living with parents, a full-time digital nomad — across the US and India, to see how housing control shapes people's relationship to space.
Riskiest Assumption
"People value understanding the 'why' behind a suggestion, not just receiving a directive." If that turned out to be a design-literate bias rather than universal, the whole premise would need rethinking.
What surprised me
| Finding | Detail |
|---|---|
| Universal impact | Every participant tied their space to mood, focus, or relationships — one traced arguments with her husband to a wall she'd painted deep red. |
| Light beat everything | 5 of 6 named lighting, unprompted, as a mood/focus factor. |
| Regret was common | 5 of 6 described a purchase or change that didn't work as expected. |
| Reasoning won | All six wanted the why, not just a directive — regardless of design background. |
| Commerce diverged | 4 wanted product suggestions optional; 1 wanted automatic; 1 warned of "a confusing mess" from too broad a scope. |
Competitive landscape
A SWOT pass against DecorMatters, Houzz, IKEA Kreativ, Planner 5D, and DecAI found the same gap everywhere — each generates a new design or sells a catalog, but none diagnose the room you already have, and none explain their reasoning. DecAI, the closest direct competitor, drew consistent complaints about generic, boilerplate output — exactly the trust problem this project needed to solve for.
Two personas, from six voices
Affinity-mapped in FigJam twice — once by theme, once re-sorted into persona-building buckets — to let two distinct people emerge cleanly rather than one muddy composite.
Define
Only after the interviews and personas did the real problem statements surface — not something I walked in with.
Problem 1 — The Self-Guided Beginner
Someone newly motivated to improve their home leans on trends and purchases as a stand-in for real judgment — without understanding the specific conditions in their own room (light, airflow, materials) that generic advice can't account for.
HMW help them diagnose what's specifically not working in their space — and why — before they default to a trend or purchase?
Problem 2 — The Design Enthusiast
Someone with some design literacy has been burned before by generic, one-size-fits-all advice that didn't account for their room's actual conditions, and is skeptical a new recommendation could be any different.
HMW build justified trust in a room-specific recommendation from the very first interaction?
Feature roadmap (MoSCoW)
Must-Have
- Photo Audit
- Reasoning-First Overlays
- Environmental Breakdown
- Lesson Cards
- Diagnosis-Based Suggestions
Should-Have
- Photo Privacy Controls
- Optional Suggestions + Budget Filter
- Before/After Preview
- Two-Way AI Chat
- Audit History
Won't-Have
- In-App Checkout
- Designer Marketplace
- 3D Room Builder
Each column maps directly to research: Must-Haves answer the problem statements directly; Should-Haves answer specific participant requests; Won't-Haves were cut deliberately to avoid the feature sprawl one participant warned about.
Information architecture
Sitemap and user flow, built before any wireframing, to lock the page-vs-card rule and navigation structure ahead of visual design.
Structural decisions
- Autosave (silent, constant) vs. "Finish Audit" (single deliberate action) — obvious on paper, not obvious to users, as testing later showed.
- Page vs. card rule — only the Lesson card stays an overlay; anything with more than one entry point becomes a full page.
Brand
Five values, pulled from research: Grounded, Insightful, Honest, Attuned, Nurturing. Japandi-restrained — the calm comes from restraint, not emptiness, since Sasha specifically craves negative space.
Color palette
Severity markers kept separate from the brand palette so diagnosis never reads as decoration:
Typography
Wireframes
Sketched every screen on paper first — some questions still open ("PAGE or CARD?" scribbled next to the Lesson screen) — then built clickable mid-fi in Figma and tested via Figma Make before any visual design work began.
High fidelity
Rebuilt every screen at full fidelity across four tasks: Audit + Learn, Next Steps, Ask a Follow-up + Finish Audit, Learn a Topic. The always-visible "Ask a follow-up" input answers Rohini's need for depth; tap-to-reveal reasoning on every finding answers the single most validated research insight.
Usability testing
Two moderated, remote, think-aloud rounds — mid-fi before visual design, hi-fi after — to separate structural issues from ones visual polish alone could fix.
| Metric | Mid-Fi (7 participants) | Hi-Fi (5 participants) |
|---|---|---|
| Flows tested | 5 task flows | 4 consolidated task flows |
| Completion | 100% (all 5 flows) | 100% (all 4 flows) |
| Unaided completion | Passed target on all 5 | Missed on "Learn a Topic" — 3/5 (60% vs. 80%) |
| Correct first tap | Passed target on all 5 | Passed target on all 4 |
| Avg. SEQ (ease) | 4.3 – 4.9 across flows | 4.6 – 5.0 across flows |
| Biggest complaint | "Show different lessons" felt random (5/7) | Suggestions missed when collapsed (3/5) |
| What held up | Audit → findings flow intuitive for all 7 | Color-coded severity praised unprompted |
Round 1 — Mid-fi (7 participants)
- All 5 flows passed (2 missed duration targets — narration/prompt confusion, not usability).
- Biggest complaint (5/7): "Show different lessons" felt like untrustworthy randomization.
- 5/7 misread numbered suggestion/lesson lists as sequential steps.
- 1 participant missed "Continue Last Audit" — a real first-tap failure, fixed by color, not layout.
- What worked: audit → findings flow was intuitive for all 7; 6/7 said suggestions felt optional, not pushy.
Round 2 — Hi-fi (5 participants)
- 100% completion on all 4 flows; "Next Steps" was clean across every metric.
- But "Learn a Topic" missed its unaided target outright — only 3/5 (60% vs. 80% target) completed it unaided, despite a perfect 5.0 ease score.
- 3/5 could use "Finish Audit" but couldn't explain what it does — discoverable, not comprehensible.
- Mid-fi fixes held: numbered-list confusion dropped 5/7 → 1/5; "Continue Last Audit" failures dropped to zero.
- Praised without prompting: color-coded severity, optional-feeling suggestions (5/5), budget filter fit, before/after comparison.
Iteration — screen by screen
Each flagged screen became its own before/after pair, with the reasoning written down so nothing changed on instinct. A smaller 5-participant before/after survey confirmed these read as real improvements, not just changes.
Audit Results
Finding Detail
Product List
Learn — Lesson Search
Lesson Card
Every reworked screen, together
Final results & reflection
- Validated: real appetite for a product that explains the why behind design, not just a redesign or a shopping cart.
- Biggest challenge: the "learn first, then act" mental model was unfamiliar at first — this product needs stronger onboarding than I scoped.
- What I learned: the Japandi-calm aesthetic was right, but people wanted more visual life — video, warm color pops. I also stopped seeing onboarding as friction and started seeing it as infrastructure.
- What I'd change: prioritize onboarding from day one; build micro-interaction animation during hi-fi, not after.
- Next steps: a real onboarding flow, a short personalization step, closing the micro-interaction gap.
I'm most proud of delivering an MVP that met its objectives, and taking the initiative to run follow-up surveys validating my own design iterations.
My architecture and civil-engineering research background is what let me treat this capstone as a research problem first — and how I found the real gap: the missing why behind design decisions, and its direct line to environmental wellness.