Empathize

Appeals to fashion enthusiasts with a massive selection and discovery tools but struggles with overwhelming options and inconsistent user experiences.

T H E P R O B L E M

Finding Sale Items

Complex sale sections make finding the right item difficult

R E S E A R C H G O A L

“We aim to identify the barriers that prevent users from effectively finding personalized fashion deals. This will inform the development of a mobile-responsive platform that helps users discover and engage with meaningful online shopping experiences.”

The research uncovered key challenges and opportunities in online shopping habits through interviews with five diverse participants. Common pain points included difficulty filtering by size, balancing affordability with quality, and tracking sales efficiently. Participants expressed strong interest in curated sale feeds, high-quality visuals, and personalized features like countdown timers and sharing options. By addressing these needs, the proposed app can streamline the shopping experience, enhance user engagement, and build loyalty among time-conscious shoppers.

The competitor analysis evaluated four major luxury fashion platforms: Net-a-Porter, LYST, SSENSE, and FARFETCH. Each caters to a unique target market, from high-end luxury consumers to young, fashion-forward shoppers. Key strengths included exceptional curation, extensive product selection, editorial content, and global reach, while common weaknesses involved high pricing, inconsistent user experience, and logistical challenges. The analysis highlighted opportunities for integrating innovative features like price tracking, AI-driven feeds, and tailored sales alerts to better compete in the luxury fashion space.

• Prioritizing user feedback helped shape critical features like personalized feeds, clear filters, and bookmarking, ensuring the app directly addressed user needs.

• Iterative design allowed for incremental improvements, with each round refining usability and validating the app's direction.

• Starting with low-fidelity wireframes simplified early testing, focusing on functionality over visuals and gathering actionable insights quickly.

• Concentrating on core features like deal discovery and personalized shopping ensured the app stayed aligned with its primary goal.

• Continuous user testing reinforced a feedback-driven approach, enabling meaningful enhancements and fostering long-term user satisfaction.

This site map offers a clear and user-friendly structure for the Finds app, prioritizing intuitive navigation. Key actions like searching, exploring curated “Finds,” and managing profiles are neatly organized into distinct sections. Filters and categories, such as clothing and shoes, make it easy for users to find what they’re looking for quickly. The flow from product details to shop and stores ensures a seamless shopping experience. Overall, this design simplifies the user journey while supporting efficient browsing and decision-making.

The high-fidelity mockups for the Finds app reflect significant improvements informed by user testing. Key updates include a clearer home page with actionable guidance, enhanced filter visibility, and a streamlined process for selecting brands and sizes. The addition of a gender selection option and a save/bookmark feature directly addresses user feedback, making the app more intuitive and user-centric. These refinements ensure a smoother, more personalized shopping experience, aligning with the app’s mission to simplify deal discovery and meet user needs effectively.

The Finds app focuses on two key user flows: Finding shopping options and prices and Curating personalized sale feeds. These flows are vital to helping users discover the best deals efficiently. The first flow allows users to easily browse products, compare prices, and access details to make informed decisions, saving time and effort. The second flow delivers tailored sale items based on user preferences like size and style, ensuring a personalized shopping experience. Together, these flows simplify the process of finding quality items at great prices, aligning with the app’s goal of making deal discovery seamless and user-focused.

Mobile native experience

After User Testing

The core features of the Finds app were prioritized to address user needs and streamline the shopping experience. Features like responsive design, advanced filtering, and personalized sale feeds were selected based on user feedback and research to help users quickly find relevant deals and enhance convenience. High-quality visuals and easy sharing options were included to improve engagement and make shopping enjoyable. These essentials align with the app’s mission to simplify deal discovery while creating a seamless and personalized user experience.

These low-fidelity wireframes represent the core user flows identified earlier: Curating personalized sale feeds and Finding multiple shopping options and prices. They are a vital tool for testing and validating user preferences in the early stages of design. By focusing on functionality over aesthetics, these mocks allow us to quickly gather feedback on navigation, usability, and feature relevance. This iterative process ensures that key elements, such as setting up preferences and browsing curated options, align with user expectations and improve the overall experience before moving to high-fidelity designs.