Sunday, August 3, 2025
Must Wants reimagines the home-buying journey by addressing the emotional disconnect of traditional listings, where "on-paper" specs often fail to match the reality of living in a space. To solve this, I designed an AI-driven platform that introduces a unique "dating" mechanic, allowing users to simulate lifestyle scenarios like hosting dinner or a morning routine—to test compatibility before ever stepping foot inside. Leveraging a hybrid workflow with Figma and Cursor for rapid prototyping, the resulting interface transforms a typically transactional search into an engaging narrative, ultimately reducing wasted tours for agents while empowering buyers to make data-backed, emotionally intelligent decisions.
Role: Lead Product Designer (Research, UX/UI, Frontend Collaboration).
Tools: Figma, Cursor, Lovable AI (AI Dev), Miro, Jira.
Story: Faced with a cluttered mobile app experience, I crafted intuitive wireframes and user flows in Figma,simplifying property browsing for users. This streamlined navigation, reducing task completion
time by 25% and boosting engagement by 30% through persona-driven design.
Compatibility Score Acceptance Rate: ≥85% of homes presented with an AI Compatibility Score>8.0 are added to a user's "favorites" list.
Time-to-Offer Reduction: Reduce the average number of homes toured before an offer is submitted by ≥30% compared to the industry standard/current process.
Platform-Attributed Sales Conversion Rate: The percentage of users who start a search on the platform and successfully close on a home is ≥3% (industry average is often lower).
Problem Statement
"Traditional home-buying platforms rely on cluttered, transactional interfaces that focus solely on 'on-paper' specifications, creating an emotional disconnect and a high volume of wasted tours because users cannot visualize their lifestyle—such as hosting or morning routines—within a space before visiting."
Business Goal: Build an AI-powered platform to streamline home buying, boosting engagement and conversions through personalized matches.
User Goal: Enable homebuyers to find compatible homes through "dating" simulations rather than manual filtering, ensuring high-confidence agent tours.
Initiative 2:
Student Digital Identity & Transcripts (EdTech/Web3)
The Challenge: Bridging the gap between complex decentralized technology and the fragmented landscape of student assets (transcripts, IDs, and resumes).
The Solution: I redesigned a mobile identity app that simplified verification flows, reducing user friction by 25%. Through rapid 2-week sprints and a modular design system, I achieved a 30% increase in feature adoption among the 18–24 demographic and a 22% improvement in wallet setup completion, balancing "Gen Z" aesthetics with professional credibility.
Demographic Adoption: Applied Gen Z mental models to the UI, driving a 30% increase in feature adoption among the 18–24 demographic.
Friction Reduction: Redesigned decentralized verification flows, reducing perceived user friction by 25% for high school and college students.
Onboarding Success: Improved digital wallet setup task completion by 22% through iterative usability testing and a modular component architecture.
Category:
Product Design
Client:
MustWants
Duration:
1.5 years
Location:
Remote
