The Problem
Through user research interviews with 18–25 year-olds, we identified three recurring pain points that made getting dressed every day more stressful than it needed to be.
01
Choosing an outfit takes too much time and mental energy, especially when balancing a busy academic schedule.
02
Limited budgets make it hard to explore new styles or buy pieces that truly work together — leading to underused wardrobes.
03
Choosing the right outfit for the right occasion — interviews, dates, social events — is a persistent source of anxiety.
{Solution}
01
Use AI technology to generate outfits based on occasions and personal preferences
{Solution}
02
Digitize personal items into 3D objects and enable virtual try-on to save time
{Solution}
03
Instagram-like community to get inspired from around the world
As a design student with a business minor...
I wanted to go beyond just incorporating nice features
and add something that can benefit the business.
So, I added an in-app shopping feature to enhance the
user experience and contribute to the overall benefit of
the business.
↓ ↓
{Solution}
04
Shop owners can share products as 3D objects for users to virtually try on. This helps users establish a deeper connection with the product, enabling better conversion. Additionally, by adding items to the wishlist, users can shop within the app.
01. Research
We conducted five user interviews with current college students aged 18–25.
3 main pain points:
Competitive Analysis
I researched some competitors' app to find inspiration. What I took away were:
Nike Virtual View
Nike Virtual View on FinishLine.com lets shoppers preview clothing on 3D holograms of models in WebAR.
Strengths
Weaknesses
Acloset
Acloset is an AI-powered fashion app that helps you manage your closet, create outfits, get style recommendations, and buy and sell pre-loved clothes.
Strengths
Weaknesses
Aiuta
Aiuta is a fashion-tech app that uses AI to help users express their personality through style.
Strengths
Weaknesses
02 — Ideation
We began with low-fidelity sketches and peer collaboration sessions to explore a wide range of interaction models. Ideas were stress-tested against our research findings before narrowing down to a core user flow.
The user flow was mapped across five key pages — covering the complete journey from onboarding through AI generation, virtual try-on, community browsing, and closet management.
We mapped out the system and divided it into 5 sub pages: Homepage, Explore Page, Generate Outfit Page, My Closet Page, and Profile Page.
03 — Design
Low-fidelity wireframes were created in Figma and tested with real users before any visual styling was applied. This ensured that core interaction patterns and information hierarchy were sound before investing in high-fidelity execution.
Lo-fi prototype testing revealed that users expected the AI generator to surface on the home screen — not buried in a secondary tab — and that the closet management flow needed to be reordered to match mental models around getting dressed.
User Testing Takeaways :
User Testing Takeaways :
04 — User Testing
Three participants completed moderated usability sessions — conducted both in-person and remotely via Zoom. Tasks covered the full product journey: onboarding, outfit generation, closet management, and social browsing.
User Interface
Sign Up Page
Explore Page
Home Page
My Closet Page
Generate Outfit Page
05 — Hi-fi Prototype
06 — Reflection
Throughout the process, I learned that user testing is key to UX design, and asking the right questions will keep me on the right track because we are designing for the users, not for ourselves. I challenged myself to think of many iterations and test them with users. I found talking to my users very enjoyable because every time I can learn a new perspective from them and discover a new way to solve the problem. If I have more time, I would continue to gather user feedback and make improvements.