Sleek Tech • 2023-2024
29 users, 3 methods – Navigation IA built around how customers actually think
Project summary
Sleek Tech is a B2B corporate services platform operating across Singapore, Hong Kong, Australia, and the UK. Their customer app navigation had never been tested against users, and as new services were being added to the roadmap, the product team needed a scalable information architecture (IA) grounded in how customers actually thought.
Problem
Two issues converged on the same navigation:
The existing structure would become unmanageable as new features were added.
The product team wanted to surface upsell opportunities for services customers hadn't subscribed to yet, without distracting customers who already knew what they came to do.
No one had ever asked users how they thought about these categories.
Solution
I ran a three-method study — closed card sort, open card sort, and tree test — with 29 participants via Maze in December 2023. The findings produced three conceptual groupings: company-owned information, Sleek-provided services, and further resources.
Working with the CPO and PMs, I translated these into a navigation rail and drawer design that balanced user mental models with the business's upsell goals.
Outcome
The research validated a scalable IA and flagged placement decisions that required senior stakeholder input.
Engineering implementation was paused in May 2024 in favour of a Vue3 migration; the designs remain handoff-ready.
My role
I led research and design end-to-end, collaborating with the Head of UX/UI, a Senior UX/UI Designer, Platform Engineering, and product leadership up to CPO level.
