Consumer IQ

Consumer IQ aggregates vast amounts of purchasing and behaviour data across thousands of retail categories. The challenge was translating that density into a platform where analysts and executives alike could surface insights quickly — without drowning in complexity.

The existing product suffered from information overload: dense tables, inconsistent chart patterns, and a navigation architecture that made cross-category comparison nearly impossible. Users were spending more time decoding the interface than understanding the data it contained.

My role covered end-to-end product design: from discovery research and information architecture to visual design, prototyping, and handoff — working in close collaboration with the product and engineering teams throughout.

The core tension: Consumer IQ's value proposition is built on data depth, but depth inherently creates visual noise. Showing everything means users see nothing clearly. The design problem was fundamentally about progressive disclosure — revealing the right information at the right level of granularity.

Key challenges identified through user research:

• 01 Users couldn't compare metrics across product categories in a single view
• 02 Chart types were applied inconsistently — the same data rendered differently in different sections
• 03 Filtering was buried three levels deep, slowing down the most frequent user task
• 04 No clear information hierarchy — everything competed equally for attention

The process started with a three-week discovery phase — interviewing seven analysts and four executives who used the platform daily. The goal was to understand not just what people did, but what decisions they were trying to make and where the current product got in the way.

From research, I developed a clear information architecture built around task flows rather than data categories. The navigation was restructured from a content-centric model (organised around what data exists) to a job-to-be-done model (organised around what users are trying to find out).

A unified data visualisation system was established — consistent chart patterns, a defined colour encoding for categories, and a typography scale optimised for reading numbers at a glance. Every visual decision was documented in a component library built to scale across future data types.

The redesigned platform launched to Consumer IQ's enterprise client base with a significant reduction in time-to-insight for common analyst tasks. The restructured navigation and persistent filter system addressed the three most frequent usability complaints from the previous version.

The new design system became the foundation for all subsequent feature development, giving the engineering team a consistent component vocabulary and reducing design-to-development handoff friction considerably.