Reimagining the Target App Homepage Experience

Problem
As digital commerce continued to drive the majority of retail growth, Target launched its Site Experience Evolution initiative to strengthen its position as America's favorite discovery destination. The company recognized that future growth would depend on delivering a more engaging, relevant, and differentiated digital experience that increased both product discovery and conversion.

A critical component of this effort was reevaluating the Target app's information architecture and homepage experience. Existing navigation patterns—including search, category access points, fulfillment options, and bottom navigation—had evolved over time, creating questions about whether guests could efficiently find products they were actively seeking while also discovering products they didn't know existed. The challenge was to optimize the experience for both findability and discoverability, ultimately increasing engagement, category exploration, and long-term customer retention.

Context
As Lead UX Researcher embedded within Target's digital strategy org, I owned the end-to-end research workstream for one of the most visible consumer-facing surfaces in Target's ecosystem — a high-stakes, fast-moving sprint with direct executive visibility and a clear tie to enterprise-level revenue goals.

Methodology
Designed a mixed-methods program combining moderated usability testing, concept testing of competing homepage and navigation architectures, and behavioral data analysis (clickstream, engagement heatmaps) to triangulate between stated preferences and actual navigation patterns. Integrated AI-augmented synthesis tooling to compress analysis cycles without sacrificing interpretive depth.

Impact
+5% Homepage CTR
+15% Category page visits
+90% Essentials tab engagement
Research findings directly shaped homepage architecture decisions and feature prioritization. Demonstrated that consumer mobile app research — when mixed-methods are properly sequenced — can drive measurable, funnel-level outcomes within a compressed sprint cycle.