Exploring experience-first wellness design through a 0—1 mobile MVP
Moments is an experience-first wellness reflection app designed to help people capture and reflect on what matters to them—without metrics, streaks, or pressure.
View prototype
Role
UX/UI Designer
Timeframe
4 weeks
Methods
User Research / Concept Development / Competitive Analysis / Wireframing/ Prototyping / Testing
The Problem with “Wellness Tracking”
Wellness is deeply personal and looks different for everyone. A morning hike could energize one person and exhaust another, while a family picnic feels restorative to some but overwhelming to others.
Yet many existing apps often prescribe wellness for users through metrics, streaks, and predefined categories, reducing complex lived experiences into numbers. There is an opportunity for a flexible approach that allows individuals to define and reflect on what wellness means to them on their own terms.
Designing for Meaning, Not Metrics
Instead of tracking moods or habits, Moments uses a context-based, low-effort approach that shifts focus from performance and consistency to reflection and meaning.
Through a lightweight documentation and reflection approach, users can discover patterns over time through energy, experience, and contexts.
Product Highlights
Experience-first, not mood-first
Moment-based, not time-based check-ins
Feelings are an optional context, not required data
No streaks and no pressure to log daily
People Want Personalized Wellness Support
Competitive Analysis
Competitive analysis explored a variety of tools from mood trackers to gamified wellness apps to freeform notetaking apps.
User Interview
I interviewed five participants who used to, are currently, or would like to track and document their wellness. Interviews ask open and nonjudgmental questions that focus on users’ general awareness, intentions, and behaviors instead of specifically how they track or document their wellness:
What is something that you do that makes you feel proud or accomplished about your well-being?
What does consistency look like for you?
Are there any other things in your life that help you stay aware of your well-being (people, routines, environment…)?
Interviews revealed that users want to better understand themselves through simple, integrated tools, each with their own approach to reflection and tracking.
“I want to know how I feel and what happened throughout the day.”
“I want to do better at reflecting on good moments than negative ones.”
“I appreciate an app that does one thing without any fluff.”
The Core Frictions:
Lacking Meaning, Organization, and Compassion
Pain point 1
Require high effort or commitment
“The mood tracking requires daily check-ins but doesn’t bring any value.”
Pain point 2
Too disorganized to find past info
“Headspace's meditation was helpful, but it wasn't intuitive to revisit the ones I have done.”
Pain point 3
Streaks feel pressuring and create guilt
“Feels like filling out a checklist.”
Based on research insights, I identified an opportunity to explore context-first reflection as a more human and engaging alternative to metrics-based tracking.
A Shared Need:
Groundedness with Minimum Effort
Personas
Among the interviewees, some people only track when something important happens, others track their habits religiously, while some with irregular lifestyles want to document and understand their lifestyles better, but don’t know where to start.
The personas reflect the diverse users I interviewed:
The intuitive yet anxious overthinker who wants to reflect more
The diligent tracker who looks for simple, low-effort tools
The busy ground seeker who is trying to be more aware but hasn't found their habits in that yet
The common ground the three personas share is that they all look for some groundedness that helps them feel more connected to themselves and understand themselves better at minimum effort.
From HMW Questions to MVP Features
I brainstormed potential features for How Might We (HMW) questions, including:
How might we help users reflect on wellness without requiring daily consistency?
How might we design a tool that brings emotional relief and clarity without relying on trackers, metrics, or streaks?
How might we reduce commitment, setup, or streak pressure that makes tracking feel like a chore?
From Research Findings
to Core Features
💡 Research Findings
—>
users want to capture meaningful moments in a short amount of time
—>
quick, low-effort reflection entry with minimal required fields
users want to be able to see past inputs/experiences with better organization
—>
view past entries: users can view past entries by clicking on tags or time filters
users want to understand their behavior and emotions so they can build long-term awareness and healthy habits
—>
simple insights based on user input
User flows
I intentionally kept the user flows simple to reduce cognitive load and lower the barrier to quick reflection and capturing what’s meaningful to the user.
Design Principle:
Contexts over Metrics
Rather than defining what wellness is to users, Moments treats energy, experience, and emotions as optional context rather than required metrics.
This approach gives user the perspectives, language, and tools to document what matters to them, rather than focusing on labeling/naming, which increases friction.
Simplicity is Intentional to Reflect Brand Essence
Moodboard
I wanted to capture a sense of authenticity and that wellness isn’t perfectly curated, but integrated into real life, drawing inspiration from the complementary worlds where real moments happen and the naturally messy, busy daily life.
Branding
The goal of Moment's branding is to create a visual that feels grounded and human, and mirrors real everyday life.
The earth-toned color palette aim to inspire groundedness and presence.
The soft and subtle blues evoke a sense of lightness and clarity.
The typography and colors all aim to be readable and approachable, not trendy or clinical.
Wireframes
Low-fidelity wireframes and testing
Low-fidelity wireframes were designed to help users capture meaningful moments with minimal effort.
Initially, I planned for fully customizable tags to give users maximum control. However, after user interviews, I realized that fully customizable tags may lead to inconsistency and way too many tags that reduce the quality of insights.
To avoid overwhelming users while still allowing personalization, I chose AI-assisted tag suggestions with user-editing. I tested AI-assisted suggestions with user editing as a middle ground, which proved successful in usability testing. Users appreciated the structure while still feeling in control.
—>
✏️ Design responses
users expect “mood” as an anchor to the experience and mood tracking as an expected feature
—>
added the optional “What emotions came up for you?” field with low UI visual hierarchy in the Capture screen
too many speaker icons create visual clutter
—>
removed the field-level voice icons and kept the main voice capture button
“low” and “high” in the energy scale are confusing
—>
changed to “draining” and “energizing”
"Capture the Moment" as a main CTA needs to be more visible
—>
added an option to add a moment on top of the dashboard (behavioral nudges instead of visual shouting)
High-fidelity Wireframes and Prototype
I created a visual hierarchy using color to make the "Capture a Moment" action more prominent in the bottom navigation. I also added an option to either speak about the moment or fill out the form manually to reinforce the idea of minimum effort.
I thought deeply about data visualization in UI, especially what I want the user to understand from the Insights page. In the quadrant insight, I decided not only show individual dots but also aggregated data visualization to show trends and actionable insights that promote awareness of patterns, rather than obsessing over individual moments
Energy & experience weekly chart
Monthly experience map
High-fidelity Wireframe Testings
Participants
5 users who are currently or used to track and document their wellness
Method
Moderated remote and in-person testing
Prototype
High-fidelity Figma interactive prototype
Tested flows
Capture a moment: focuses solely on adding a moment and filling in the required information
Edit a past moment and add more details: focus on if use can edit and add more details by clicking the expandable feature
View monthly insights
Each flow is relatively simple is to focus on whether users can complete the core functions of this app.
What worked well
Task completion rate: 100%
Overall ease of use rating: 9.4/10
Feature usefulness and relevance rating: 10/10
Key areas for improvement
Make interaction obvious
💡User signal
All usability testers attempted to move the slider directly, revealing an affordance issue
✏️ Action
To support quick, intuitive reflection, I kept the Edit icon and replaced the slider with icon inputs
Shift from evaluation to reflection
💡User signal
The labels “energy level” and “experience level” felt metric-focused and unclear
✏️ Action
I reframed them as quick reflection prompts:
“The moment was…” (draining ↔ energizing)
“The moment felt…” (unpleasant ↔ pleasant)
Before
After
Clarify product intent, reduce misinterpretation
💡User signal
Rating scales led users to interpret the product as a mood tracker
✏️ Action
Kept energy and experience scales as optional inputs to preserve insight value without defining the experience
Surface emotional expression earlier
💡User signal
Users wanted stronger emotional context
✏️ Action
Moved emotion tags from the expandable section to the main entry flow
Increase user control over AI assistance
💡User signal
Automatically adding generated tags felt invasive rather than helpful
✏️ Action
Shifted to user-initiated input by promoting media upload and replacing auto-added tags with a “+” affordance
Before
After
Final Wireframes, UI Kit, and Prototype
High-fi with usability test feedback expanded personalization and emotional connection. This development makes sure the app supports awareness and grounding before layering additional complexity.
View prototype
Finding Middle Ground in User Insights
Users said they didn’t want rigid mood tracking, but they still crave emotional connections and grounding. I learned to find the balance that holds both truths by adding the “What emotions came up for you?” question with suggested tags, positioned as context, instead of required data.
Low-effort Doesn’t Mean Minimum Use Engagement
I assumed that users don’t want to input too many fields and options but testing showed that users want rich contexts, such as media, feelings, and customizable tags. I learned that the solution wasn’t removing features but rather making them optional, relevant, and progressive.
AI Assists, Not Dictates
My first approach had AI auto-adding the tags, which felt invasive to users. I learned that AI works best when it suggests rather than decides for users. Users want to feel in control even with external help.