Structure
Problem:
Parents struggle with decision fatigue while dressing toddlers each day.
Parents repeatedly described mornings as:
rushed
mentally overloaded
full of micro-decisions
time-constrained
Selecting outfits from a large wardrobe made mornings even harder.
Every additional item multiplies complexity
4 tops×4 bottoms×4 shoes=64 decisions before 8am
Insights from Research
Parents want speed, reliability, and fewer decisions, not more options.
Easy access to trendy yet comfortable outfit ideas
Personalized suggestions that fit their child's preferences
Features that help plan light and plan effortlessly
Do not want to waste time browsing for multiple stores for outfit ideas
Confusing size charts and ill-fitting purchases
Overpacking for trips due outfit uncertainty
Stress from last minute outfit planning
Constraints
Interaction must be effortless, parents use the app during stressful moments.
Parents won’t manually catalog every item
Setup must feel lightweight
Utility must be accessible in one tap
Avoid complex filtering
Outfits must feel “thoughtful,” not randomly generated
Key Decision 1: Daily Outfit Recommendation
Replace manual entry with AI-driven outfit recognition.
Users upload or scan a garment. The system automatically:
Identifies garment type
Suggests season + occasion
Tracks fit as the toddler grows
AI reduces setup friction and organizes wardrobe automatically.
Key Decision 2: Make Upload a Global Action
Removing Upload CTA reduced task completion friction.
Early testing showed forcing users into a dedicated upload tab and having a dedicated upload CTA increased friction. In addition, grid-column garment layout and filter options presented too many choices to the user.
The upload/scanning function was integrated into a persistent global action within the wardrobe(as seen in following section).
Upload item CTA was integrated into Virtual Wardrobe
Key Decision 3: Trigger-Based Predictive Outfitting
Selecting one garment auto-generates a compatible outfit.
Instead of browsing entire catalogs, parents select one piece.
The AI provides:
Style match scores
Fit type
Compatible items
Virtual Fit Features
Single selection → full outfit combinations
Decision shifts from browsing to reviewing.
Browse by event, style and trending picks
Key Decision 4: Designing Around Event-Based Planning
Parents think in events, not categories.
Research showed parents plan by:
Birthday
Playdate
Wedding
Festival
Design System Foundation
Powered by a Scalable Design System
The interface is powered by a reusable token-based system covering color, typography, spacing, and reusable UI components.
Key Decision 5: Home as a Decision Command Center
Reduce search time by surfacing what matters first.
The home screen prioritizes:
Daily recommendations
Recently added items
Smart notifications
Parents move from searching → deciding in seconds.
Key Decision 6: Integrate Memory with Wardrobe
Prevent repetition and support milestone tracking.
The Memories Hub organizes content through:
Event tags
Facial recognition filters
Milestone grouping
Memory management solutions
Wardrobe becomes both planning tool and archive.
Solution
A structured AI wardrobe that minimizes daily cognitive load.
The final system:
Automates garment classification
Predicts outfit combinations
Surfaces event-based recommendations
Tracks growth
Keeps utility one tap away
Outcome
Demonstrated measurable reduction in friction across core flows.
Reduced time spent selecting outfits
Improved clarity of outfit suggestions
Less emotional stress during mornings
Clearer understanding of matching and seasonal wear
Reflection
Designing for stressed users requires absolute simplicity and clarity.
This project taught me how to design for users under time pressure, using psychology and simplicity to reduce decision fatigue and increase confidence.