TEAM
Sunny Lee - UX Design
Angela Argentati - Product Management
Justin Morgan - Solutions Architect (iOS)
Andrew Bradnan - iOS Development
Harrison Shapley - Android Development
Alexander Biemann - Android Development
Mike Gourdin - Quality Assurance
Jonathan Bergeron - UX Research
Amy Roark - UX Copywriter
Dave Kover - UX Standards
Vidhya Subramanian - Accessibility
DURATION
15 months
CLIENT
Best Buy - Seattle Technology Development Center
TOOLS
Sketch, Zeplin, UserTesting, UserZoom, InVision, MIRO, Keynote, 3DStudioMax, VRay, Blender, Reality Composer, Photoshop, Illustrator, After Effects, Lottie, Optimizely, Adobe Analytics, OpinionLab, and JIRA.
PLATFORMS
iOS: ARKit, SceneKit, RealityKit, QuickLook
Android: ARCore, Sceneform, ModelViewer
OVERVIEW
To address a surge in TV returns caused by fit-related issues under Best Buy’s 15-day return policy, the company formed an augmented reality (AR) team on October 1, 2018. The team aimed to reduce losses by helping customers select appropriately sized TVs. I joined the team on February 12, 2019, shortly after the launch of their iOS minimum viable product (MVP).
A look at the MVP of the app when I joined the team. It is a representational TV, and not a true 3D model. The stand underneath the TV is an estimation, and caused confusion with users.
3D MODELS
Developing our first set of TV models required six months of development from initiation to completion. I established an evaluation framework to assess six potential partners based on modeling and texturing capabilities, quality, cost, speed, and real-time geometry optimization.
CONCEPT DEVELOPMENT
I began by creating low-fidelity paper prototype screen flows to address key user needs. The user flow integrated key functionalities, including an entry point, virtual object placement, object dimensions, price and size comparisons, and photo capture for shared purchases.
.
PLACEMENT HELP
Initial testing showed low virtual TV placement rates. A/B tests revealed tutorials improved placement but increased drop-off, so I added an on-demand tutorial button which boosted placement without hurting engagement.
Onboarding illustrations by Sunny Lee. Copy written by Amy Roark and Angela Argentati
CUSTOMER FEEDBACK
With engineering resources limited and usability testing unavailable, I partnered with data analytics to deploy OpinionLab’s feedback form that captured insights without waiting for internal support.
Our goal was to collect actionable feedback efficiently. To maximize engagement, we kept the feedback question concise. Within the first two weeks, we received over 800 responses. Notably, nearly 20% of comments contained actionable feature requests, which I organized into an affinity map.
DYNAMIC MESSAGES
Based on usability test observations and customer feedback, I developed the first set of dynamic messages for “pre-placement” events. These messages guided users through the virtual object placement process by analyzing light, space, and user progress.
Animated in After Effects and exported with Lottie’s Bodymovin plugin
We also introduced “post-placement” messages. They were concise hints that helped users refine their TV placement. These appeared on the first launch and dismissed upon action completion.
SHARED ANALYSIS
To further assist decision-making, we added a photo feature, allowing users to capture and share snapshots of their scene.
LESSONS LEARNED
After implementing the redesigned UI and enhanced 3D models, we saw a 6-8x increase in average session duration. This signaled how immersive design directly boosts user engagement.
While features like ‘save for later,’ photo sharing, and dimension tools didn’t directly boost revenue, they significantly enhanced engagement and buyer confidence, which were key drivers for long-term adoption.
CASE STUDIES
VIRTUAL TRY-ON
BESPOKE SERVICES
SMART CAMPUS
SHARED VISION