01
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 lost sales.
02
The Challenge
Online apparel shopping is full of hesitation: guesswork, high return rates, and inconsistent sizing across brands. Shoppers can’t confidently predict fit or feel before buying, which costs retailers real revenue in returns and abandoned carts.
Sizing is inconsistent across brands
A "medium" fits differently depending on the retailer, leaving shoppers to guess or size up and hope for the best.
Static photos can’t show fit or drape
Product photography shows the garment on a model, not on the shopper’s own body, leaving a gap between expectation and reality.
Returns erode trust and margin
Fit-related returns are among the most common and costly in apparel e-commerce, driving up cost for both shopper and retailer.
03
My Approach
I started by framing the business and user problem through research, then narrowed in on the feature requirements: 3D body scanning, a fit rating system, virtual try-on, multi-item search, one-tap checkout, customizable preferences, and clothing variations across cut, silhouette, and appearance.
Behavior
Online Shopping Habits
—Shoppers order multiple sizes and return what doesn’t fit
—Sizing anxiety drives cart abandonment
—Reviews and Q&A are used as fit substitutes
Concern
Sizing & Fit
—Fit terminology varies wildly across brands
—Body shape isn’t reflected in standard size charts
—Shoppers want to see fit before purchase, not after
Interest
Virtual Try-On
—Strong interest in AR/3D try-on tools
—Shoppers want realistic draping and movement
—Willingness to share body measurements for accuracy
Loyalty
Brand & App Preferences
—Loyalty follows fit confidence, not just price
—Shoppers stick with retailers that get sizing right
—App convenience influences repeat purchases
04
The Solution
I developed personas, ran a competitor analysis, and moved through user flows, wireframes, and rapid prototypes. Then I conducted usability testing to gather feedback on onboarding, shopping, virtual try-on, multi-item search, and checkout.
Personas & Competitor Analysis
Persona #1 - Lindsay, the Shopaholic
Persona #2 - Jeff, the Routine Online Shopper
Wireframes
Early sketches for onboarding and shopping preferences
Rough layouts for the photo capture, try-on, and cart flow
Early checkout, payment, and account screens
Initial concepts for shop, inspiration, and fit-score screens
Prototype
Users capture a quick photo scan to power accurate fit predictions.
Shoppers select their favorite retailers to personalize their in-app experience.
Shoppers search and filter for items across each of their selected retailers.
Items are tagged Perfect Fit, Okay Fit, or Not for You based on the shopper's saved measurements.
The AR try-on view lets shoppers see themselves virtually wearing the items they've selected.
A one-tap checkout consolidates items from multiple retailers into a single cart.
What Changed
Before, and after.
Before
Shoppers guessed at sizing from flat product photos and static size charts.
After
AR try-on lets shoppers see clothing on their own body before buying.
Before
Fit language was inconsistent: "loose," "tight" meant different things to different users.
After
A standardized fit rating system (Perfect Fit, Okay Fit, Not for You) replaces guesswork with clear labels.
Before
High return rates from fit mismatches ate into margin and buyer trust.
After
Try-before-you-buy confidence is designed to reduce returns tied to sizing.
05
What this solved.
—
A quantitative 0-100% fit score was tested first, but usability testing revealed it felt confusing and arbitrary to shoppers, so it was replaced with a clearer qualitative scale: Perfect Fit, Okay Fit, and Not for You.
—
3D body scan calibrated against each retailer’s own size specs, not a generic chart.
—
Store-specific section headers, rewards status, and order numbers added to reduce multi-store checkout confusion.
—
emBODY positioned in a market gap: high immersiveness and fit accuracy that competitors don’t yet offer together.
Specialties Shown
Turning a business hypothesis into a tested, buildable product.
User Research
Competitor Analysis
User Personas
Task Analysis
User Flow
Wireframing
Rapid Prototyping
Usability Testing
UI Design
Product Strategy
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