Commercial Analytics Hub

The Commercial Analytics Hub is an internal platform I designed and built to centralize access to dozens of enterprise analytics dashboards. Before it existed, finding the right report could take over an hour. After launch, most users could get where they needed to go in under a minute. It became the primary starting point for more than 1,000 people across the organization.

This project is a good example of how UX isn’t always about making new tools—it’s often about making existing tools usable, trustworthy, and easy to find.

The problem

Analytics access was messy. Dashboards were scattered across Power BI workspaces, SharePoint sites, and personal bookmarks. Links changed often and without warning. Ownership was unclear. New hires and occasional users had no reliable way to learn what to use or where to go.

Power users survived by memorizing paths and saving bookmarks. Everyone else lost time clicking broken links, searching old emails, or messaging coworkers for help. People regularly spent more time finding dashboards than using them.

The real issue wasn’t the dashboards themselves. It was discovery, trust, and clarity.

Goals

From a user perspective, the goal was simple: find the right dashboard fast, know which one to use, and trust that it would actually work. From a business perspective, the goal was to create a single source of truth for analytics access, reduce wasted time, and increase confidence in data usage.

There wasn’t a complicated success metric. If people didn’t use it, it failed.

My role

I owned the project end-to-end. I led research and stakeholder interviews, defined the product vision, designed the information architecture and UX, designed and built the UI, maintained the front end, and managed stakeholders through multiple iterations. Aside from a small team that helped with backend chatbot integration, I owned design, UX, and front-end development.

Research and insight

Through interviews and behavioral analysis in FullStory, I saw a clear split between user types. Power users had built their own systems: bookmarks, memorized workspace paths, and direct navigation. Occasional users had no such system. They bounced between SharePoint sites, clicked outdated links, and messaged teammates for help. Some spent hours just trying to find the right report.

When I analyzed click paths and hesitation points, a simple pattern emerged: users didn’t need better dashboards. They needed a single, trusted place to start. Fragmentation—not complexity—was the root cause of wasted time and low confidence.

Information architecture

I organized dashboards by type of analysis—market share, assortment, revenue management, shelf planning, promotions, and more. This matched how analysts already thought about their work and reduced cognitive load.

I explored organizing by questions like “How do we grow market share?” but rejected it. It was too subjective, hard to scale, and required interpretation. Instead, when dashboards overlapped, each entry included a clear description, when to use it, and what level of detail it provided. That removed the need for tribal knowledge.

Key design decisions

Rather than trying to fix navigation inside Power BI or SharePoint, I built a dedicated access layer whose only job was clarity and discovery. Dashboards were clearly separated from power-user data tools so non-technical users didn’t land in workflows they couldn’t use.

The experience was designed for browsing. Clear categories, scannable descriptions, and predictable navigation made it easy to explore even if you didn’t know what you were looking for yet. Trust was built through consistency: links stayed current, changes were communicated, and the hub became the single authoritative source.

Training and enablement

Training used to disappear after live office hours. Once a session ended, the knowledge was effectively gone. I changed that by recording sessions, embedding videos directly into the platform, and labeling them by topic and dashboard.

What used to be temporary became an on-demand knowledge base. New hires could onboard themselves, occasional users could refresh their memory, and anyone could learn independently without waiting for a live session.

Iteration and evolution

The first version was a simple MVP built in Webflow to validate adoption. Usage quickly proved there was demand.

In the second phase, I expanded the platform by adding training content, improving the information architecture, and aligning the visuals more closely with the internal design system.

As the site grew, Webflow became a bottleneck. Global changes required page-by-page edits, and shared logic was hard to manage. I rebuilt the platform in React to centralize logic, improve performance, and make iteration faster. Users explicitly noticed the speed and clarity improvement.

In its most mature phase, the hub fully aligned with the enterprise design system and reusable components. It became a reference model that influenced four to five other internal platforms.

AI search and Analytics Academy

To reduce friction even further, I integrated a natural-language chatbot. Instead of browsing categories, users could ask something like, “Where do I find promo performance for Target?” and get a direct link.

I also helped launch the Analytics Academy, a role-based learning system with live sessions, recorded content, and structured learning paths. All of it lived inside the hub, so learning and doing were never far apart.

Impact

The platform reduced dashboard discovery time from about 60 minutes to about 1 minute. It reached more than 1,000 active users within a few months and was adopted organically across teams. Trust in analytics improved, and the platform became a reusable model adopted by other groups.

One of the most common things I heard was: “It’s the first thing I open every day.”

Reflection

This project pushed me to grow from designer into a true UX engineer. By owning both design and implementation, I reduced handoff friction, iterated directly on user feedback, and built faster with more confidence.

More than anything, it reinforced what I care about most: great UX isn’t just about interfaces. It’s about clarity, trust, and making people’s work easier every day.