HaloX Product Audit

HaloX Product Audit

⚠️ CONFIDENTIALITY NOTICE⚠️

This case study contains work on a product that has not yet been released. To maintain confidentiality, specific details and visuals have been blurred or omitted.

HaloX Network Graph

HaloX Product Network Graph

Role

Role

UX Designer

Platform

Platform

Web Application

Web Application

Timeline

Timeline

3 weeks

About HaloX & Its Users

HaloX is a suite of data analytics tools that helps users unlock value from public data, images and video, commercial geospatial imagery, unstructured text, or any combination of these. Using various AI technologies, it delivers actionable insights for its users.

The primary users are government and defense teams, who rely on geospatial and public data for strategic decisions, and commercial organizations, who analyze diverse data sources to drive business outcomes. HaloX empowers professionals to extract insights efficiently and make informed decisions.

THE PROBLEM

Data visualizations are difficult to understand

Data visualizations are difficult to understand

HaloX’s mission is ambitious: turning massive streams of public, geospatial, and unstructured data into insights. But during my audit, I noticed a recurring problem. The interface often overwhelmed users, especially in high-stakes government and commercial contexts. Complex visuals and unclear interactions slowed down decision-making drastically. For example, the network graph lacked hover interactions, forcing users to click into potentially dozens of nodes to view information. My goal was to uncover these friction points and propose clear, intuitive solutions.

THE PROCESS

Heuristic Analysis: Uncovering key usability issues

Heuristic Analysis: Uncovering key usability issues

My audit revealed several usability breakdowns:

  • Lack of responsiveness: key elements, like nodes, didn’t provide feedback on hover or click, leaving users unsure if their actions had an effect.

  • Inconsistent symbols: icons varied in style and meaning, making it harder for users to form reliable mental models.

  • Hard-to-read visualizations: dense graphs and charts made it difficult for users to quickly interpret data relationships.

These issues made the platform difficult to navigate and often frustrated users, particularly due to the lack of feedback on interactions.

Redesign Spotlight: Making the network graph readable

The network graph was a core feature but initially hard to interpret. My redesign focused on two main improvements:

Interactive node popups

Interactive node popups

Interactive node popups

Hovering over a node now shows a popup with key information. Users can expand this popup to view full details. Connections between nodes are also highlighted, making relationships immediately clear.

Note: The original design cannot be shown due to sensitive information.

User Node Popup

Displays a user’s profile across various social media platforms.

Video Node Popup

Shows a video URL along with information about who posted it.

Community Node Popup

Highlights connections between users, giving a clear view of group relationships.

Side menu overhaul

Side menu overhaul

Side menu overhaul

I redesigned the filter and control menu to be more intuitive and easier to navigate. I’ll showcase several iterations of the menu I designed to illustrate the design thinking process.

Option 1

The 'Show Labels' button appears to only apply to Users.

Option 2

Menu styling isolates the user from the other node types.

Option 3

Successfully indicates that labels apply to all items on the graph.

Impact: Making Complex Data Instantly Understandable

Impact: Making Complex Data Instantly Understandable

The redesign allows users to quickly interpret the network graph without clicking into every node. Hover popups surface key information instantly, connections are clearly highlighted, and the side menu makes filtering intuitive. These improvements reduce cognitive load and let users from all backgrounds efficiently explore and extract insights.

These enhancements let users scan and interpret complex graphs at a glance. Overall, the platform becomes faster, clearer, and more actionable for all types of users.

FINAL THOUGHTS

Reflecting on this project

This project reinforced how critical clear, interactive design is when working with complex data. Even powerful analytics tools can become frustrating if users struggle to interpret information quickly. By focusing on hover interactions, intuitive popups, and a streamlined side menu, I learned how small design choices can dramatically improve usability and efficiency. Moving forward, I’m motivated to apply these principles to ensure that data-driven platforms are not just functional, but also accessible and engaging for all users.