Hi, I'm Marc Woo.

Product designer shaping the next generation of search and discovery.

I specialize in search and complex navigation, helping millions of users find exactly what they need.

Search and Navigation Architecture

Dick's Sporting Goods · 2022 – Present

I re-architected the foundational logic for product discovery, transforming a fragmented legacy schema into a single, adaptive system. This design foundation reduced technical debt and enabled intent-based retrieval for millions of queries.

Mobile Menu Optimization

Cut exit rates 30% by minimizing decision fatigue.

I overhauled mobile wayfinding, effectively reducing cognitive load while streamlining the internal taxonomy management process.

Semantic Search Experience

Translated complex ML signals into human-readable results

I designed a visual framework for Vector Search, translating complex ML predictions into transparent, trustworthy results, even for vague customer queries.

Global Navigation Architecture

Eliminated layout shifts (CLS) to prioritize content discoverability.

I optimized the global header to solve layout instability and compressed navigation height by 35%, ensuring content visibility to build trust within the first millisecond of interaction.

Browse Ecosystem and Decision Support

Dick's Sporting Goods · 2022 – Present

I restructured the core browse framework to resolve ‘choice paralysis.’ By organizing complex inventory into comparable patterns, I accelerated the customer journey from discovery to conversion.

Compare Tool

Generated a 7-figure lift in profit/visit via a 0-to-1 implementation.

I normalized complex technical data into scannable, side-by-side patterns, keeping the discovery loop internal and reducing external "tab-switching."

Geospatial Health Mapping for IoT System

Novosselov Research Group · 2021 – 2022

I designed the companion interface for AeroSpec, a portable IoT sensor system that transforms raw environmental telemetry into intuitive, actionable health signals. This architecture allows users to discover hyper-local safety trends through high-fidelity geospatial visualizations.

Interactive Discovery Logic

Prioritized immediate safety signals over raw data.

I designed a tri-state snapping bottom sheet to manage high-density telemetry, surfacing immediate "Safe/Unsafe" status first while disclosing granular pollutant metrics only upon user interaction.

Privacy-First Spatial Indexing

Abstracted precise locations into community-level signals.

I architected a hexagonal grid system leveraging Uber’s H3 index to resolve the "utility vs. privacy" trade-off, protecting contributor anonymity without sacrificing mapping resolution.