At CarMax, I led the end-to-end research and redesign of the geolocation experience to better guide users to the right cars at the right locations. Our goal was to create a more accurate, user-centered location flow that connected customer intent with store availability while informing smarter operational decisions.
The initial proof of concept, adding a simple “See cars at this store” interaction—led to a 4000% increase in engagement. This early success reduced customer friction, surfaced regional demand insights, and built momentum for a full geolocation platform redesign adopted across product teams.
Geolocation
Success Metrics
Defined and tracked performance across three key performance indicators:
User Engagement
Goal: Improve accuracy of store-level vehicle views.
Metric: Engagement with location dropdown and “See cars at this store” interactions.
Result: 4000% increase in engagement post-implementation.
Demand Accuracy
Goal: Capture more accurate location intent to support in-store visits.
Metric: Increase in store visits linked to geolocation updates.
Tools: Mobile app analytics, door entry, sales data.
Target: 10% increase in store visits from location-based actions.
Supply Chain Optimization
Goal: Identify car movement needs based on user demand by region.
Metric: Increase in relocations driven by geolocation signals.
Tools: Website behavior tracking, Qualtrics surveys, and ongoing qualitative research.
Target: 30% increase in location-based relocation of inventory.
Design Opportunity
User Problem
Desktop users without a set store or ZIP code were automatically geolocated via Akamai.
Akamai redirected them to a data center, not a nearby CarMax store.
Users mistakenly thought they were viewing local inventory, causing frustration and drop-off.
Business Problem
Prior geolocation efforts were deprioritized in favor of other initiatives, leaving stakeholders dissatisfied.
Incorrect location data misinformed supply chain decisions, limiting operational efficiency.
A better geolocation experience could surface more accurate demand, reduce relocation costs, and improve conversions.
Key Decisions & Process
Discovery + Strategy
As Senior Product Designer on the DotCom brand team, I led the geolocation initiative from kickoff through implementation. I began by creating experience maps and facilitating a three-hour design thinking workshop to uncover gaps in the legacy system.
To inform prioritization:
Analyzed Adobe Analytics data to uncover behavioral patterns and engagement gaps
Reviewed call center logs and user flows to identify common user pain points
Built dashboards to visualize insights and support decision-making
Conducted 1:1 interviews with product owners, engineers, and designers to surface cross-team dependencies
Gathered historical context to align priorities and inform cross-functional collaboration
Top User Journeys on DotCom
GPS Touchpoints Across the Dotcom Experience
Collaborative Research
To ensure the redesigned geolocation experience aligned with real user needs, I led a structured research initiative that combined qualitative insights with agile validation methods. Our goal was to understand how users prioritize information when selecting a store and to surface pain points in the existing flow. These efforts informed design decisions, improved content hierarchy, and helped reduce friction in the location-selection process—ultimately supporting higher engagement and more accurate demand signals for the business.
Research Methodologies:
Card Sorting (Unmoderated): Facilitated exercises where users ranked key content elements (e.g., maps, services, timing) to understand content priorities.
Ethn.io Recruitment + Usability Interviews: Targeted users were invited for one-on-one sessions to explore motivations, expectations, and pain points in the geolocation flow.
Indi Young’s “Lightning Quick” Method: Used short, focused usability tasks directly on the live site for fast, in-context feedback.
Agile Iterative Testing: Ran lightweight, continuous usability tests to validate evolving design decisions and de-risk implementation.
Original Find A Store in Main Navigation
First test of Nearest Store component
Last test of Nearest Store component
Moodboard Collection of North Stars
Implementation & Team Enablement
Led a 5-month rollout of the new experience, building momentum across product and engineering teams.
Boosted research participation across departments by 40%, driving shared ownership.
Reduced cross-functional blockers by 25% through bi-weekly syncs with mobile, buyer, and seller teams.
Coached a junior designer to lead 50% of the deliverables and co-present at two internal town halls, ensuring sustainability post-contract.
3 Concepts for Redesign of the Store Page
Learnings
Design-Led Collaboration Creates Momentum
Cross-team research and early involvement unlocked deeper buy-in and increased long-term adoption.
Rapid Testing Accelerates Decision-Making
Lightweight, iterative testing methods allowed us to validate concepts without delaying dev cycles.
Small Wins Drive Systemic Change
A single micro-interaction test led to enterprise-wide conversation about rebuilding the geolocation platform.
Coaching Is Strategy
Enabling junior team members to lead and present deepened team capacity and created leadership continuity beyond the project handoff.
Explore More Case Studies
Explore More Case Studies
Explore more projects that showcase the breadth of my design leadership
From personalization and GPS-based experiences to extended reality (XR) and enterprise-scale ecosystems, each case study highlights a unique facet of how I lead research, strategy, and user-centered solutions that drive meaningful impact.