2025
Na
⚡Background
Loomé is a fashion-tech mobile app currently under development that uses an AI-powered quiz-based personalization system to recommend outfits tailored to users’ preferences. Unlike existing players such as Stitch Fix or Wishi, Loomé aims to be affordable, transparent, and inclusive, blending AI efficiency with human stylist input. The MVP focuses on creating a mobile-first experience for users to discover styles aligned with their personality, budget, and lifestyle.
🚨Problem Statement
Fashion personalization today faces several challenges:
Overwhelming choices on e-commerce platforms make decision-making stressful.
Limited inclusivity in terms of size, style, and cultural diversity.
Lack of transparency — users don’t know why certain products are recommended.
High costs for stylist-led platforms like Stitch Fix.
Loomé’s goal is to solve these gaps by designing a mobile-first, quiz-driven fashion assistant that feels engaging, reliable, and accessible.
📊User Research & Discovery
Competitive Benchmarking:
Stitch Fix: Personalized but expensive, limited reach.
Wishi: Heavy on human stylist input, low automation.
Retailer Apps (H&M, Zara): Catalog-heavy, lacking true personalization.
User Research (Ongoing):
Interviewed 15+ fashion-conscious users aged 18–30.
Key findings so far:
70% prefer interactive quizzes over browsing endless catalogs.
65% want budget-conscious personalization.
80% said they want to know why an item was recommended.
🎯Design Goals
Create an engaging, quiz-first onboarding flow.
Deliver personalized recommendations with clear reasoning.
Ensure mobile-first accessibility with simple navigation.
Support inclusive styling (sizes, budgets, cultures).
Build a strong MVP foundation for future scaling.
🧭Design Process
The design process is structured in iterative phases:
Information Architecture: Mapping quiz → recommendation → stylist refinement → save/share.
Wireframing (Mobile-first): Low-fidelity sketches for quiz flow and product cards.
Visual Design: Light, fashion-forward UI with soft gradients and modern typography.
Prototype (Ongoing): Interactive mobile prototype in Figma for usability testing.
🎨Solution & Final Design
Current Progress
Onboarding Quiz: Conversational flow capturing style, fit, color, and budget preferences.
Recommendation Feed: Personalized outfits with explanation tags like “Because you like bold colors”.
Stylist Notes: Optional human stylist input to refine suggestions.
Saved Styles: Users can bookmark or share looks.
Profile: Stores preferences, sizes, and style history for future recommendations.
Low-fidelity wireframes for the quiz flow and product feed are completed.
Information architecture mapped for MVP.
Visual direction (warm, modern, fashion-forward) finalized.
High-fidelity prototypes for onboarding quiz are in progress.
User testing (upcoming): Initial feedback to refine the recommendation logic and flow.