My role
Sole Data Vizualization Designer
Team
Product Operations Manager: A. Tamalonis, UX Designer: M. Ivy
Audience
Our UX Design team: A. Tamalonis, M. Ivy
Duration
1 week
Software Used
Tableau
Scope
Key metric prioritization and definition, data visualization design, dashboard information architecture, component-level UI redesign, atomic design system integration, visual hierarchy optimization, semantic color mapping
The Problem
Our UX Design team had no place to see product performance at a glance. Without a shared dashboard, standups, brainstorming meetings, and stakeholder reviews relied on scattered reports, making it difficult to identify which metrics actually drove product decisions. It also made it difficult to remember where we pulled a metric from. We also had to have faith that the product managers and data team would pull the data that was actually useful to us. They usually did, but we needed more user-behavior-centered data that explicitly captured how clinicians interact with content and what they are looking for in real time.
The Approach
I defined a set of priority metrics that aligned with business outcomes. Those were conversion rate, error rate, user engagement, and task completion. Then I filtered out data that was available but we couldn’t act on. I then mapped each metric to a chart type based on what the data needed to communicate. For instance, for the user engagement rate, I used a line chart to show trends over time. For all the other data points, I used single metrics for current status.
The existing Quantum Metrics dashboard treated all metrics with equal visual weight. I rebuilt the components in Figma using our atomic design system. I gave the user engagement chart the spotlight by placing it at the top left corner, since this is the metric our team lives by or dies by. Also, I gave conversion rate, returning visitors, bounce rate, and error rate greater prominence through larger type, larger cards, left placement, and semantic color tokens. For metrics that displayed time, I changed the unit of measurement from seconds to minutes, as that’s easier for my team to comprehend.
To deeply capture user intent, I introduced two new behavioral modules to the lower half of the dashboard framework. First, rather than relying on flat page views, I designed an article action bar engagement module using a horizontal bar chart to track key article actions like print, share, copy, upvote, and save. I even matched the icons from the article page. This provided the team with an instantly scannable, ranked view of high-intent user interactions. Second, I integrated a search intent data table displaying the most common search topics, such as CPT, digital health, and public health, which surfaced immediate user trends and allowed the team to proactively audit our information architecture.
The Outcome
The redesign was not built due to engineering capacity constraints and lack of business buy-in, but it helped our team get an idea of which metrics were important to us, and which metrics we were measuring success by. It aligned product management and stakeholders with our vision of success.
