Mattel Reporting Dashboard

Fixing a Broken Experience: How UX Saved a Multi-Year Client Relationship

The Problem

Mattel, one of our key Tier 1 clients, had been with us for nearly two years but was growing increasingly frustrated with our SaaS platform. The platform’s choppy, unintuitive design forced their team to navigate across multiple tabs just to manually compile key KPIs for daily reporting.

These inefficiencies led to mounting dissatisfaction, placing Mattel’s account at risk. The urgency to resolve these issues intensified as we faced an imminent threat of losing their business. To retain this critical client, we needed to deliver a seamless, efficient reporting experience—fast.

To retain this critical client, we needed to deliver a seamless, efficient reporting experience—fast.

My Role

As the Lead Business Analyst and UX Designer, I was responsible for driving the design strategy, stakeholder communication, and data analysis to ensure a seamless reporting experience for Mattel.

My role required balancing user needs, product constraints, and business priorities, ensuring that the final solution was both intuitive and technically feasible. I worked across strategy, execution, and cross-team coordination, ensuring that design, data, and business goals were aligned for maximum impact.

I collaborated closely with cross-functional teams, including:
🔹 VP of Analytics – Aligning data insights with business objectives.
🔹 UI Designer – Translating UX strategy into a polished visual interface.
🔹 Two Project Managers – Managing sprint priorities and development timelines.
🔹 Retail & Media Specialist – Ensuring industry-specific reporting accuracy for Mattel.

The Challenge

The client’s renewal deadline was approaching at the end of the quarter, intensifying the urgency to deliver a solution. With only five weeks to execute, if we didn’t act fast, we risked losing the client entirely.

The challenge was twofold: I needed to deliver a seamless reporting experience while also aligning with product sprint priorities and engineering timelines. Balancing design updates with development feasibility meant that every decision had to be strategic to fit within the constraints of our existing roadmap.

For me, this created an aggressive scope, requiring tight coordination across teams while ensuring that design, product priorities, and engineering efforts remained in sync.

Stakeholder Analysis

Understanding Key Players & Communication Strategy

Before directly jumping into the project, I needed a clear understanding of who the key stakeholders were and their priorities, since there were multiple stakeholders invested in its success. To ensure consistent and timely communication across all groups, I conducted a stakeholder analysis to map out key players, their interests, and how best to engage them throughout the project.

Stakeholder Analysis: Power-Interest Grid

Stakeholder Communication Plan

Based on the Power-Interest Grid analysis, I developed a structured communication plan to ensure the right level of engagement for each stakeholder group. The plan outlines communication frequency, methods, and key messaging tailored to each group’s level of influence and interest in the project.

With a clear understanding of who the key stakeholders were and their priorities, I moved forward with in-depth stakeholder interviews to gather insights on their pain points and expectations.

The Framework

Stakeholder Interviews: Understanding Key Perspectives

I conducted qualitative research through stakeholder interviews and user observations. This helped uncover critical pain points, guiding the design decisions that improved usability and efficiency.

Internal Client Service teams - one-on-one, 30-minute interviews with key internal stakeholders—those who had worked closely with Mattel and had firsthand knowledge of their frustrations over the course of the engagement
Client team at Mattel - a 45-minute deep-dive session with Mattel’s team, including the VP of Global Media and Director of Omnichannel Retail.

Key Insights from Stakeholder Interviews

I synthesized user feedback into three major themes:

I also recorded how long it took users to complete tasks:

Defining User Roles: Aligning UX with Real Workflows

After analyzing stakeholder needs and conducting interviews, I identified distinct user roles that defined how different stakeholders interact with the dashboard. Roles would help me focus on my users’ functional responsibilities, their context of use within the system and specific tasks and goals that need to be achieved, ensuring the design aligns with real-world usage.

The Design Evolution

Low-Fidelity Mockup

To ensure alignment early in the process, I began with a low-fidelity mockup to gather client feedback before moving into data integration. This approach minimized the risk of major revisions later and demonstrated tangible progress, reinforcing client confidence that their concerns were being addressed.

Client Walkthrough & Feedback

I conducted a guided walkthrough of the low-fidelity prototype, focusing on:

Information hierarchy: Ensuring the most critical KPIs were positioned prominently for quick insights.
Navigation flow: Highlighting how users would interact with filters, KPI cards, and charts.
Dashboard usability: Testing whether key interactions aligned with client needs and reporting workflows.

The session provided valuable real-time feedback, allowing me to refine the design before investing in high-fidelity visuals or data integration.

I felt this step was key, as the feedback revealed previously unspoken requirements that had not surfaced in initial discussions. These insights played a significant role in shaping the final design, ensuring it aligned more closely with user needs.

Mid-Fidelity Mockup

Building on insights gathered from the low-fidelity prototype, I developed a mid-fidelity mockup. This iteration introduced more refined layouts, interactive elements, and a clearer representation of the final data structure while still allowing room for feedback and iteration.

Key Enhancements from Low-Fidelity to Mid-Fidelity

Updated Date Filters – Providing more flexibility to capture events such as Prime Day
Interactive Elements Introduced – Mockups now included basic interactions to simulate filtering changes and data updates.
Functional Prototype Testing – Used this iteration for internal stakeholder testing, ensuring the design met business and user needs before moving to high-fidelity.

Key Outcomes & Business Impact

The final iteration of the KPI reporting design resulted in measurable improvements across usability, efficiency, and client satisfaction.

Enhanced Executive Decision-Making (Marketing Director Focused)

50% faster insight retrieval due to clear KPI cards and YOY % change visibility.
Increased confidence in data with an intuitive, at-a-glance dashboard.
More informed strategic decisions by quickly identifying brand and retailer trends.

Improved Data Analysis Efficiency (Media Analyst Focused)

60% reduction in Excel exports due to in-platform dynamic filtering and interactive charts.
30% faster deep-dive analysis, as users could instantly see deltas and breakdowns.
Increased accuracy in reporting through near real-time data visualization updates.

Stronger Cross-Team Collaboration

Analysts could quickly provide data-backed insights to Marketing Directors, reducing back-and-forth requests.
Customizable date ranges and dynamic charts allowed users to tailor insights for different stakeholders.

Learnings & Next Steps: Evolving the Dashboard for Greater Impact

Key Learnings

Balancing Simplicity & Depth Is Critical

The challenge was creating an interface that was simple enough for executives yet detailed enough for analysts.
Solution: Layered data approach with high-level KPI cards and deeper drill-down options.

Interactivity Drives Engagement

Users engaged more with data when they could interact with KPI cards, update charts dynamically, and filter results easily.

Stakeholder Alignment Enhances Adoption

Early involvement from Marketing Directors, Analysts, and IT Teams ensured the tool met all user needs.
Continuous feedback loops led to an iterative design approach that increased adoption rates.

Next Steps & Future Enhancements

Introduce Predictive Analytics: AI-powered insights that automatically flag anomalies in performance metrics.
Expand Data Visualization Options: Introduce more interactive chart types, such as trend lines and comparative overlays.
Optimize Performance & Data Loading Times: Work closely with Data Engineers to bring in datasets to scale to other retailers.