Problem
75% of Gen Z & Millennials desire to buy from sustainable brands, but only 25% actually do.
"How might we bridge the intention-action gap and empower consumers to make sustainable apparel their lifestyle choice?"
People want to shop sustainably. They don't know where to start. Gen Z and Millennials experience cognitive dissonance: they care deeply about sustainability, but their actual shopping behavior doesn't align with that care.
The problem isn't a lack of intent; it's the existing platforms that add cognitive load rather than reducing it.
Solution
An AI retail platform that integrates your existing wardrobe with personalized recommendations.
The gap between wanting sustainability and buying sustainably isn't about values: it's about mindset and friction.
Stori removes that friction through four interconnected experiences: AI starts with your existing wardrobe, generates outfit combinations, identifies actual gaps, and then recommends from vetted brands. Users make fewer, better purchases, and mindful consumption becomes a lifestyle choice rather than an effortful endeavor.
Tell us what matters to you
Stori learns about you by capturing your style, values, and sustainability priorities, building a personalized profile that makes every recommendation feel made for you.
AI capability: PREFERENCE LEARNING captures nuanced user inputs across values, habits, and goals.
Explore
Discover sustainable brands through need-first browsing…
Search how you think: "work trip to Miami", "casual brunch", or "winter night out". Effortlessly discover diverse styles and collections from vetted sustainable fashion brands tailored to your unique style and preferences.
AI capabilities: CONTEXT-AWARE SEARCH (NLU) + HYBRID RECOMMENDATION interprets natural language and generates personalized collections.
Educate
Make informed decisions before purchase
Make an informed decision before clicking "buy now". Every product shows verified impact data, with AI-generated outfit recommendations.
AI capabilities: NATURAL LANGUAGE PROCESSING (NLP) verifies sustainability claims + STYLE COMPATIBILITY generates outfit recommendations
Curate
Maximize your wardrobe's potential
Engages with your digital wardrobe or visualizes endless combinations on your virtual self without worrying about size, fit, or style.
AI curation and recommendations form existing wardrobe nudges towards mindful need-based consumption.
AI capabilities: COMPUTER VISION (CNN) digitizes wardrobe + STYLE COMPATIBILITY MATCHING generates outfit combinations
Connect
Stay inspired beyond the purchase
Individual behavior change is hard to sustain alone. Through community engagement, rewards, and collaborative features, you stay committed and inspired towards your journey.
AI capabilities: CONTENT RECOMMENDATION + BEHAVIORAL TRACKING personalizes challenges and community content.
Role
As the sole designer on this project, I conducted research with 20+ consumers and brands, applied BJ Fogg's Behavioral Model to identify intervention opportunities, and designed the end-to-end experience across four pillars. Focused on understanding why users hesitate, why decisions overwhelm, and how design can make sustainable choices feel natural.
Research
Researching why good intentions don't translate to action.
I started by asking why consumers say sustainability matters, but still buy from fast fashion brands. What are the barriers that prevent them from acting on their values?
I delved deep into understanding consumer behaviors, what their current purchase experience looks like, where it breaks down, and what barriers they face when trying to shop sustainably.
Key finding
These six challenges don't work in isolation. Using BJ Fogg's behavior model, I synthesized that they function as a connected system where Ability, Motivation, and Prompt all fail at once.
Mapping Users by Mindset, Not Demographics
I realized that traditional personas (such as age, income, and location) wouldn't be helpful here. What matters is what drives someone and what blocks them, and that changes based on the category and moment.
Market positioning and core offerings
Existing platforms solve one challenge but ignore the system.
Through competitive analysis and brand interviews, I discovered no platform combines personalization, wardrobe integration, verified sustainability, and AI assistance in one seamless experience.
My positioning: What if we eliminated that trade-off?
Stori sits in the white space
High on both axes, combining convenience & personalization with transparency & sustainability.
AI makes this possible
It eliminates manual effort (digitizing wardrobes, learning preferences, and personalizing recommendations) while maintaining trust (through verified sustainability and transparent impact).
Design decisions
Designing for Real People, Real Friction
Understanding the system failure wasn't enough: I needed to design solutions that worked for real behavior, not ideal scenarios.
I iterated on various options, continuously testing with people around me to understand what felt natural versus what added friction. Through this process, two core design decisions emerged that would define how users actually experience Stori.
The result
By simplifying the process of making responsible fashion choices, Stori bridges the intention/action gap, promoting a behavioral shift toward mindful consumption.
Impact
Stori demonstrates how AI can humanize sustainable fashion, connecting personal style, ethical awareness, and digital intelligence without forcing users to compromise.
What This Established:
Framework connecting consumer behavior challenges to AI solutions
"AI as assistant" interaction model for implicit learning
Wardrobe-first design pattern reducing overconsumption
Design principles for behavior-change platforms
Recognition: Received a design award affirming its relevance as a forward-thinking model for technology-enabled mindful living.
Reflection
Let Research Lead, Not Assumptions
Early in the project, I had strong opinions about what users needed. But forcing myself to validate every assumption through research revealed insights I wouldn't have found otherwise, like wardrobe-first being more important than I initially thought.
Always Return to the "Why"
When design challenges arose (should AI be conversational? how to structure recommendations?), I learned to anchor decisions back to research insights.
Trust the Process, Apply the Right Tools
This project taught me that structured design thinking, using the right research methods at the right time, and reflecting systematically, transforms complex problems into clear, actionable solutions.