CONCEPT VALIDATION & UI DESIGN

emBODY

    Goals

    • To design a mobile app that allows online shoppers to virtually try on clothes using augmented reality (AR).
    • Through the use of this mobile app, online shoppers will be able to make more confident purchases, resulting in a lower return rate for companies and decreased costs.

    Skills

    • User Research
    • Competitor Analysis
    • User Personas
    • Task Analysis
    • Wireframing
    • User Flow
    • Rapid Prototyping
    • Usability Testing

    Overview

    emBODY is a mobile app concept designed to help online shoppers virtually try on clothing using augmented reality (AR). The goal was to reduce uncertainty around fit, increase buyer confidence, and create a more efficient shopping experience that could also help retailers reduce returns and related costs.

    Challenge

    Online apparel shopping often comes with hesitation, guesswork, and high return rates because shoppers cannot confidently predict how clothing will fit or look in real life. The challenge was to design a digital shopping experience that addressed fit anxiety, supported style discovery, and reduced the need to jump between multiple retail websites or apps.

    My Approach

    I started by framing the business and user problem through secondary research, then narrowed the focus to fashion and apparel shoppers. I conducted user interviews with people who shop for and return clothing online, then synthesized their behaviors, pain points, advantages, and habits. Key insights included that shoppers rely heavily on reviews, customer photos, brand familiarity, styling inspiration, and repeated store preferences, but still experience anxiety about fit and appearance.

    Strategy & Design Decisions

    I created user personas, completed a competitor analysis, and defined the product’s differentiator: a more immersive try-on experience that could work across multiple online stores. I then translated the research into feature requirements, including 3D body scanning, fit ratings, multi-store search, one-cart checkout, style inspiration, customizable preferences, and clothing variations such as tucked, untucked, buttoned, and unbuttoned views.

    Competitor Analysis

    Immersiveness: The degree to which a person's unique body measurements are being incorporated. Fit accuracy: Refers to how well the clothes are projected to fit virtually compared to how they actually fit in real life.
    • Zeekit, a start-up company founded in 2013, developed the first dynamic virtual fitting room giving every person the chance to see themselves in any item of clothing found online. The company was acquired by Walmart with the retail giant stating that the AR technology will be available "soon." 
    • Amazon aims to do something similar and is currently developing its own technology so that customers can try on clothes prior to purchasing them.
    • Style.me, Asos, and Gap all have solutions available but are limited by the shopper only being able to use an avatar based on basic measurements and generic body shape selections.
    • Uniqlo offers augmented reality mirrors which allow in-person shoppers to select and try on clothes of different sizes and colors without having to grab more clothes inside the store. The fit accuracy is low because of the rudimentary way the clothing is displayed on the person's body.
    • emBODY is positioned to have both a high degree of immersiveness and fit accuracy with the use of AR and 3D body scanning, to ensure an accurate representation of how the clothes will fit in real life, and be available for any online store which is currently a gap in the market.

    Solution

    I developed low-fidelity wireframes, user flows, and a rapid prototype that covered onboarding, shopping, virtual try-on, outfit inspiration, cart, and checkout. I then conducted an early unmoderated usability testing round with prototype users to gather feedback on navigation, perceived usefulness, checkout clarity, and the fit rating system.

    User Flows

    Wireframes

    Key Feedback & Iterations

    Prototype feedback helped identify two important improvements. First, users needed clearer language around the “fit score,” so I changed it from a score out of 100 to a more understandable “Fit Rating” system with qualitative labels: “perfect fit,” “okay fit,” and “not for you,” from comparing their 3D body scan to the clothes' specifications. Second, users needed clearer labeling during checkout, so I added store-specific section headers, rewards information, store counts, and order numbers to make the multi-store checkout experience easier to understand.

    What This Case Study Demonstrates

    This project shows my ability to connect a business problem to user needs, conduct research, analyze competitors, define product requirements, create user flows and prototypes, test the experience, and iterate based on feedback. It positions me well for teams who need someone who can help turn concepts into a clearer, testable product experience.

    ‍Specialties shown: User Research, Competitor Analysis, User Personas, Task Analysis, User Flow, Wireframing, Rapid Prototyping, Usability Testing, UI Design, Product Strategy, UX Writing, Iterative Design