Z e l i a
AI-powered app that uses AI to predict users' wardrobes, curate event-specific outfits, and provide personalized shopping recommendations.
Project overview
Summary
Zelia is an AI-poowered personal stylist and personal shopper that helps users choose the perfect outfit based on hyper-personalized recommendations.
My role
UX / UI designer
First steps
The project began with an initial MVP app version. After acceptance into Chicago Booth's accelerator's program, the team worked on refining the MVP to improve its functionality and user experience
Design process
User research
To guide the next iteration, we dove into user research. We mapped out user flows and sitemaps to streamline navigation and ensure a seamless journey, A Backlog helped us prioritize features based on user behavior and business goals.
Competitive audit
Understanding the market was also crucial to refining the product. We analyzed leading fashion wardrobe apps through a competitive audite, which helped us identify gaps and opportunities to stand out.
Key improvements identified
User research revealed areas where the experience could be improved:
-Simplified onboarding to create a more intuitive user journey
-Include AI-powered outfit suggestions feature for personalized styling
-Add a swipe-base feature to make browsing outfits more engaging
-Enhance the UI design for a cleaner, more modern aesthetic that aligns more with Gen Z's design preferences
Key mockups
After redesign, Zelia was selected for Techstar's accelerator program !
Next steps
1
Gather user feedback to identify pain points and areas for improvement.
2
Monitor app performance and KPIs - user engagement and user reviews (active users, session duration and frequency, screen time).
3
Release updates and new features regularly and bug fixes.
4
Monetization strategies - discuss potential revenue streams such as in-app purchases and sponsored content