Introduction

• Brief: Evaluate the usability of the IDB DataGov portal and deliver actionable recommendations.

• Challenge: Make complex governance data more accessible for a broad audience.

• Goals: Improve site design, affordance, cognitive load, and user feedback.

Discovery Phase

• Stakeholder interviews: Met with IDB product owners and analysts.

• Business requirements: Clear data presentation, smooth comparison flows, and better user guidance.

• User needs: Easy navigation, clarity on data meaning, and confidence when comparing indicators.

Problem Framing

• Problem: Users struggled with unclear data descriptions, visual hierarchy, and confusing query processes.

• Success: Users can confidently access, interpret, and compare governance indicators.

• Constraints: Must work for new and experienced users, no major backend changes.

User Research

• User interviews: Gathered feedback from both regular and new portal users.

• Competitive analysis: Reviewed similar data portals for best practices in data display and comparison flows.

• Market research: Found that step-by-step guidance and clear visual cues drive better engagement.

Synthesis

• Personas: “The Policy Analyst,” “The Occasional Researcher,” and “The Curious Newcomer.”

• Journey mapping: From landing on the portal to running a successful data query and interpreting results.

• Key insights: Users need better onboarding, clearer process feedback, and more descriptive data labels.

Solution Development

• Info architecture: Proposed clearer navigation and simplified data comparison paths.

• Wireframes & prototypes: Mocked up improved indicator descriptions, step-by-step query flows, and visual hierarchy tweaks.

• Visual design: Focused on hierarchy, feedback cues, and consistent labeling.

Testing

• Usability testing: Ran remote sessions with sample users on prototype flows.

• User feedback: Users found the new descriptions and step-by-step process much easier to follow.

• Iterations: Tweaked feedback messages and refined visual hierarchy based on input.

Implementation

• Handoff: Delivered annotated recommendations, wireframes, and a usability checklist to the IDB dev team.

• Dev collab: Synced with product and engineering leads for implementation roadmap.

• Go-to-market: Recommendations rolled into an upcoming portal update.

Results & Impact

• Metrics: Fewer support queries, higher successful query rates, and longer session times.

• User adoption: Positive feedback from both new and returning users.

• Business impact: Improved confidence in the data and smoother research workflows.

• Lessons learned: Little things—like better feedback and clearer labels—make a big difference in data-heavy tools.