Overview

Displayr is an advanced AI focused data insights and dashboard software used by leading market research agencies around the world. The company underwent a UI redesign in 2022 and with no design system established from the outset, over time, the software accumulated a vast amount of inconsistencies. Legacy elements, fragmented interaction patterns, engineers making design decisions, these were scattered throughout the product. I led a comprehensive UI audit to document and prioritise these inconsistencies, establishing a clear baseline from which a more consistent, scalable Displayr could be built.

The audit was broken down into structured phases, with each inconsistency logged and documented in detail in a Notion database. This was to capture everything needed for an engineer to understand, assess and action each issue. In total, 137 inconsistencies were identified, spanning dropdown behaviour, tab styles, typography, iconography and interaction patterns. Each was scored using a Cost/Impact framework, weighing estimated user pain against engineering effort. The findings fed directly into two outputs: the rules and foundations of Displayr's design system, and a UX backlog of items flagged for fixing.