Redefining Scope: From Full App to MVP
Nanomood Technologies Inc. | Startup @UCSD | UI/UX Designer
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Tools
Figjam | Figma | Builder.io | Google Docs | Zoom
Team
2 UI/UX Designer | 3 ML Engineer | Co-Founder | Founder
Timeline
9 months
My Overall Impact
As a UI/UX Designer at NanoMood, I was responsible for creating the desktop version of their existing user app. But I also helped market NanoMood to investors at startup events, reached out to hospitals to introduce the platform and gather feedback, and collaborated with ML engineers and designers to define and build the MVP end-to-end.
Overview
NanoMood stands at the forefront of digital health innovation, by using biometric data and AI, we are positioned to offer comprehensive insights and personalized solutions, paving the way for more effective and patient-centric approaches in the treatment of neurological conditions.
For the Hong Kong Techathon, our goal was to design a minimum viable product (MVP) that could communicate NanoMood’s value quickly and clearly to investors and healthcare partners. Instead of building a full feature set, we focused on creating a simple, intuitive flow that showcase the main features of the app.
Problem
Designing a Clear, Purpose-Driven MVP
The original NanoMood concept aimed to combine mood tracking, biometric data, and AI-powered insights into a single platform but it was too complex for an early prototype. Our challenge was to translate this broad vision into an MVP that clearly communicates NanoMood’s purpose and core value to both users and stakeholders.
How might we simplify NanoMood into a focused MVP that demonstrates its value to both users and stakeholders?
Nanomood MVP Highlights
The Core Features of The MVP
The NanoMood MVP focuses on simplifying how users understand their mental health through real-time biometric and mood data. Each feature was designed to make the experience more intuitive, actionable, and trustworthy.
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Onboarding: One-page demographic and data setup for faster completion.
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Profile: Central hub for remaining setup tasks like connecting devices and uploading data.
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AI Chatbot: Built-in assistant for quick guidance and support.
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Reports: Clear analytics on stress, mood, sleep, and activity data.
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Notifications: Smart alerts triggered by data changes to guide timely actions.
Brainstorming
How can we design the MVP to clearly communicate its value without requiring users to explore every feature?
During early brainstorming sessions with the founders, developers, and machine learning team, we mapped out the full NanoMood platform covering biometric data, EHR integration, surveys, and AI-driven insights. Through these discussions, we realized the concept was too broad for an MVP and needed to focus on a few essential features.
Together, we identified NanoMood’s core pillars:
- Continuous mood and biometric tracking
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Data visualization through clear, user-friendly dashboards
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Conversational AI interpretation for accessible insights
Competitive Analysis
Complex visuals make it hard for users to connect with their mental health data.
We reviewed leading mental-health and neuropsychiatric platforms to understand how they present mood and biometric data and to find opportunities for NanoMood to stand out.
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Feature Benchmarking: Real-time insights and mood tracking were standard; many used overly technical formats.
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Visual Clarity Gaps: Most platforms used dense charts or raw data hard for patients to understand.
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Opportunity for Simplicity + Trust: NanoMood could stand out with more human-centered, plain-language explanations and friendly visuals.
Heuristic Evaluation
Evaluating The Current App For Usability Issues
I conducted a heuristic evaluation of the existing NanoMood app to uncover friction points in the user experience. The analysis focused on clarity, layout hierarchy, and task efficiency across key flows like onboarding, reports, and assessments. Findings revealed opportunities to simplify data-heavy screens, prioritize actionable items on the homepage, and streamline questionnaires all of which shaped the foundation of the MVP redesign.
(swipe left to view all for mobile)
User Personas
Understanding Two Perspectives: Users & Stakeholders
To design an MVP that clearly communicates NanoMood’s value, we identified two key audiences: end users and techathon judges. Maya represents the everyday user who needs simplicity and clarity in managing her mental health, while Dr. Chen represents stakeholders looking for purpose, feasibility, and clear differentiation. Designing with both perspectives in mind helped us balance usability with strategic communication.
User Testing
We needed to understand whether the data was easy to understand
We recruited ~10 UCSD students who owned wearable devices and were interested in mental health.
Testing Scope:
We divided the user testing into three key flows for the patient platform: 1. Onboarding & Account Creation 2. AI Chatbot Interaction 3. Health Data Visualizations: Generated using LLMs developed by our machine learning engineering team to translate raw wearable data into personalized mental health insights
What We Measured:
- Task Completion: Could users complete onboarding and navigate key features independently?
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Comprehension: Did users understand their health metrics and AI-generated insights?
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Engagement: Did users interact naturally with the chatbot and find it useful?
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Satisfaction: What were the friction points, and how did users react emotionally or verbally?
Insights & Iterations
Complicated Data Visualizations & Flow From Participants & Founder
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User seemed frustrated by the multiple steps on each screen
→ During testing, participants hesitated and expressed that the process felt unnecessarily long. However, when tested with a consolidated version, no confusion or drop-off occurred
Action Taken: We combined all questionnaires into a single, fill-in-the-blank page, replacing the older multi-step design that made input a hassle.
2. User seemed frustrated by the multiple steps on each screen
→ Users were confused about what information was being collected and why.
Action Taken: Added information icons beside each data input explaining its purpose and relevance to personalized insights.
3. Complex graphs left users confused instead of informed
“These graphs are very complicated? I don’t even know how to read scatter plots.”
→ Participants felts overwhelmed and couldn’t interpret the visualizations
Action Taken: Replaced scatter plots with simpler formats and introduced a “data interpretation” section summarizing key takeaways in plain language.
4. Lack of Real-Time Alerts
“Can the app send a notification when it detects something unusual in my data?”
→ Patients wanted timely awareness of significant changes in their health metrics.
Action Taken: Built a system for tagging/confirming events and added a notification flow to flag irregular biometric patterns.
5. The data visualization needs to be more condensed
Founder: “Let’s simplify the flow by putting all data views in a dedicated Reports section. Split it into two tabs: Analytics and Metrics. So it’s faster to navigate and less confusing than scattered, detailed pages”.
Action Taken: We moved data visualizations off the home screen and into a new Reports nav item, divided into Analytics and Metrics for quicker discovery and a cleaner homepage.
MVP Final Solutions
The MVP Is Now Ready For The Startup Pitch
The NanoMood MVP app was designed to simplify how users understand their mental health through real-time biometric and mood data.
1. Onboarding & Profile
Connect your device/provider, answer brief demographics, and land on a checklist dashboard. Inline info tooltips explain why each data point is collected.
2. AI Chatbot
In-app assistant that answers feature questions and routes users to the right screen or action.
3. Reports (Analytics & Metrics)
Clear visuals for stress, depressive state, anxiety episodes, questionnaire results, sleep, steps, heart rate, and respiration with simple trend highlights.
4. Notifications
Gentle alerts when connected data shows disruptions (e.g., fewer steps, poor sleep). Tapping opens the related report with a suggested next step.
Reflection
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Speak up early
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If something feels off or too busy, say it as soon as possible. Big, ambitious add-ons can wreck flow and confuse users.
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Ask “naive” questions
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Especially with ML charts. What does this metric mean? Why include it? Where should it live? those basic questions saved us from showing data that didn’t help.
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Write everything down
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Startups move fast and memories blur. Quick notes on decisions, reasons and next steps kept everyone (founders included) on the same page.
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Check out my other projects!
Website Maintenance
NCG Website Redesign
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