Background
PrendasYa is a B2B e-commerce startup that connects clothing manufacturers with retailers and resellers, offering curated collections at wholesale prices. The goal was to modernize and digitize a highly manual and informal purchasing process common in Latin America’s textile industry. The founding team needed a product that felt easy to use, visually appealing, and accessible for users who might not be familiar with modern e-commerce interfaces.
Core problem
The business was starting from scratch, with no existing product or design foundations. The challenge was to design a UI that clearly communicated trust, simplicity, and efficiency for buyers who are used to ordering via WhatsApp or catalogs. Since many users would be accessing the platform from mobile devices, responsiveness and legibility were critical. The lack of digital literacy among some of the target users added pressure to reduce friction and cognitive load at every step of the experience.
The solution
I led the UI design for the platform, working closely with the founders to define a visual language that balanced modern e-commerce standards with the needs of a wholesale-focused audience. I designed screens for product discovery, filtering by category or price, product detail pages with size and color variants, and a simple checkout process optimized for mobile. I also defined reusable UI components to ensure consistency and scalability as the platform grows. The look and feel combines clarity, soft neutrals, and strong visuals to highlight products while building trust and usability.
Results and Impact
The design work helped PrendasYa launch its MVP and validate its value proposition quickly in the market. Early users praised the simplicity and clarity of the interface, and the visual language gave the brand a professional edge in an industry that’s still undergoing digital transformation. Within the first few weeks of launch, the platform attracted over 500 registered buyers, and the conversion rate from product view to purchase was significantly higher than expected for a first version. The system is now ready to scale and iterate based on user feedback and data.