The Challenge
What Discover Was Facing
Discover's content platform had a depth problem: users engaged with the first screen of results but rarely explored further. Scroll depth analysis combined with qualitative interviews revealed that the IA presented content as an undifferentiated feed — there was no structural signal to help users understand what types of content existed or how to navigate intentionally rather than scroll passively.
The Solution
What We Built
We ran a content audit and taxonomy research project with 90 users, using card sorting to identify the mental categories users applied when deciding what to watch or read. The redesigned IA introduced a layered browse structure with editorially curated and algorithmically personalised entry points. Wayfinding cues were embedded throughout to orient users who arrived via deep-link.
Results