B2B SaaS
Shipped
·
2026
Role
Product Designer, UX/UI
Team
PM, Tech Lead, 3–4 engineers
Timeline
Feb–Apr 2026
Company
Performance management platform
Signals
clicks on non-interactive areas
use of the Back button
clicks on “Create development goal”
Competencies
Information Architecture
Delivery & Quality
Data-informed Design
Context
The company is a B2B SaaS performance management platform. The individual report is one of the most accessed features in the product — used by employees and managers during every performance cycle to interpret results and guide development conversations.
My role
I joined the squad while the project was in progress, after discovery and the core solution direction were defined. I took over screen refinement and the handoff, worked with engineers throughout development, and ran QA together with the PM before rollout. After launch, the PM and I analyzed behavior in Microsoft Clarity.
Problem
Employees struggled to independently interpret their performance results, while managers found it difficult to use the data to guide meaningful conversations. The report lacked visual hierarchy, clarity, and context — making information hard to scan and easy to misread. The downstream effect: low engagement with the platform and weaker performance cycles overall.
Before — Scattered, hard to scan
After — Clear hierarchy, guided reading
Discovery
Research by the squad before I joined:
Methods: User interviews · Heatmap analysis · Competitor benchmarking · UX heuristics review
Volume: 66 user insights · Benchmarking against two leading HR-tech competitors · Hotjar heatmap data from 22,000+ page views
Key findings:
- Users spent most time trying to locate information rather than interpreting it
- Lack of visual hierarchy forced linear reading instead of scanning
- Heatmap data showed attention scattered across menus and secondary areas — away from core content
- Managers reported difficulty using the report as a base for development conversations
What this told us:
The problem wasn't the data — it was the structure. Users had everything they needed, but couldn't find or process it efficiently. The redesign needed to prioritize hierarchy and progressive disclosure over completeness.
How might we
How might we reorganize the individual report so that employees can independently interpret their results and managers can use the data to have more meaningful development conversations?
Solution
Applied information architecture and UX best practices to restructure the report — improving visual hierarchy, findability, and progressive reading of information.
The redesign introduced clearer content blocks organized by priority: overview first, then strengths and areas for improvement, then detailed averages. Each section guides the user through their data rather than overwhelming them.
AI integration was added to support users in interpreting results and connecting performance data to development actions.
Key decisions
The solution direction was set by the squad before I joined. I refined and delivered it:
Header with actions and tabs (Overview, Averages, Individual answers, Goals), so users see right away that they can act from the report.
Progressive disclosure: one topic expanded at a time, and actions removed from the averages table so the task there is just reading.
Answers grouped by relationship, one question open at a time.
Reference points (scale min and max, highest and lowest scores) to build mental models.
Direct bridge to development: create a development goal from inside the report.
One decision of mine: I added strengths and areas to improve to the overview, so readers get the two things they need most before reading the details.
New report layout — applying UX best practices and design heuristics to improve hierarchy, reduce cognitive load, and guide users through their performance data.
Results
One month after launch, heatmap analysis confirmed a significant behavioral shift — user attention moved from scattered navigation areas to the report's core content blocks: overview, strengths, areas for improvement, and averages. Reading became more guided and objective.
Full quantitative data is being tracked across complete performance cycles.
Share of attention by page depth, 3 months before vs. after launch (Microsoft Clarity).
What’s next
In-page usability improved clearly. Downstream outcomes, like development plans created after the report, haven’t moved yet. They’re partly skewed by large batch releases, so we’re isolating that effect before drawing conclusions. Performance cycles are semi-annual, so impact matures over the next cycles.
