As Wayfair’s product inventory grew, certain large product categories became cumbersome for users to navigate via filters and pagination alone.

For instance, more than 800,000 products were in the wall art category at the time. To help spur discovery, we explored a visual search concept where users are presented with groups of products with similar styles (e.g., color, shape, and style). The goal was to more effectively help users find the perfect item for them (the "a-ha" moment).

Utilizing a proprietary data science model, we’d allow users to drill down based on their style preferences, introducing products that may have previously been buried deep in pagination due to lack of popularity or sales.

User testing, competitive analysis, and a two-day design sprint helped guide the concept with the KPIs of improving discoverability and engagement in mind.