As Wayfair’s product inventory grew, certain large product categories became cumbersome for users to navigate via filters and pagination alone.
To help spur discovery, I explored a visual search concept where users are presented with groups of products of similar styles (i.e. color, shape, art style for wall art). 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.