Moodie
: A low-friction mood tracking app that helps busy people capture emotions and recognize patterns over time.
Project Type |
Team Project (4)
Timeline |
In Progress
My Role |
Product & UX/UI Designer
Tool |
Figma · FigJam · Lovable
Challenge
Mood tracking can feel valuable in theory but burdensome in the moment, especially when it requires users to stop and write.
Opportunity
Reduce the effort of starting while giving users a reason to return to their past entries.
My focus
Designing a fast logging flow and a lightweight feedback loop that turns individual entries into meaningful patterns.
Research
Understanding why people quit
To understand what prevents people from building a consistent reflection habit, we ran a survey and short interviews to learn when mood tracking feels useful, when it becomes a chore, and what makes people return.
87 survey responses
Too much friction to start
36
Hard to stay consistent
28
No feedback from past entries
20
No personalized guidance
12
"How might we make emotional logging feel like a natural reaction, not a task to schedule?"
Two patterns anchored our decisions: the barrier to starting was too high, and even motivated users had no reason to keep going because past entries didn’t feel worth revisiting.
Prioritization
What we built first and what we cut
Quick Wins (shipping in MVP) sit in the high-impact, low-effort zone. Everything in the lower band was considered but cut from this phase.
Shipping now
Quick Log
Log a mood in under 5 seconds, reducing the highest-friction moment identified in research.
Shipping now
One-line Entry
Add an optional, low-pressure sentence instead of writing a full journal entry.
Shipping now
Weekly Review
See a short summary that makes past entries worth revisiting.
Push Notifications
Deprioritized - Risked feeling like pressure, the exact friction we were trying to remove.
Guided journaling prompts
Deprioritized - Added more writing effort, working against the goal of a fast, low-friction log.
Social sharing
Deprioritized - Mood data is sensitive, so trust and privacy needed to come before any social features.
UX Flow
Designing around two drop-off moments
Research pointed to two exact moments people disengage: the very first log, and the point where they stop returning. I mapped the flow to remove friction at the first and add a reward at the second.
Contribution
What I owned vs. what the team owned
Moodie is a 4-person team project. Here's the breakdown, so it's clear what's mine.
User research & survey
Designed the survey and synthesized results together as a team
Claire
Pain point prioritization
Voted and ranked together using the Quick Wins framework
Team
UX flow & IA
I mapped the core journey and drop-off points
Team
Hi-fi UI design
I'm designing all screens in Figma, in progress
Claire
Current Status
Where we are
User Research & Pain point analysis - done
Solution prioritization (Quick Wins framework) - done
Hi-fi design - in progress
Development via Lovable - upcoming
User testing post-launch - upcoming
This case study is actively updated as the project evolves - from research through to launch.
