Paramount SSR+
Complex Data Reporting Tool
Self Serve Research Plus (SSR+) provides teams across the company with streamlined access to vast, complex data in a unified tool - vital for tracking, managing, and reporting how billions of dollars are spent accross Paramount’s advertising platforms.
Through my design work, SSR+ became part of a marketable, industry-first product suite, helping our research and sales teams generate granular insights faster.
Company
Paramount
Objective
Transform a complex legacy tool into a revenue-generating SaaS platform, delivering fast, granular ad insights to power billions in ad spend across Paramount
My Role
Product Designer responsible for UX research, ideation, wireframing, prototyping, testing & design QA
Timeline
2023-2024
Problem
The challenge involved replacing an outdated and overly complex data reporting tool that no longer integrated with modern systems. While the legacy tool offered extensive data customization options, its cumbersome navigation called for a complete overhaul.
Users across various teams required an upgraded solution that preserved essential customization features yet streamlined the process of deriving insights from vast, complex data. The new tool would be a central hub to manage intricate data and analytics to monitor billions in advertising spend effectively.
Legacy Tool
Research
We used a combination of interviews and usability testing to deeply understand our users' needs and pain points.
A key part of this research involved feature mapping the legacy tool to identify which functionalities users relied on most, as well as areas for improvement. This helped ensure that essential features were preserved or enhanced in the new design.
We discovered that many users had developed rigid workflows and were hesitant to explore unfamiliar features due to the tool’s complexity, while others were unaware of certain capabilities.
Users consistently emphasized the need for speed, simplicity, and reliability in generating reports and accessing insights, indicating a need for an intuitive, streamlined tool.
Legacy Tool Feature Mapping
Solution
By carefully mapping the legacy tool's features, we ensured that essential customizations were preserved, while eliminating unnecessary complexity to create a more intuitive user experience. The new tool allowed users to generate reports and access insights faster and with greater ease, all while maintaining the familiar workflows that long-time users were comfortable with.
We designed the tool to function as a central, reliable source of truth for teams across the company, accommodating the unique needs of various departments while simplifying the overall process of working with large and intricate datasets.
Redesign
Results
- Reduced time on task from 5+ minutes to less than 2 minutes, saving our teams valuable time & resources.
- Increased monthly active users by 55% 3 months after launch.
- Reduced onboarding time for new users by 23%.
Reflection
This project highlighted the importance of thoroughly understanding complex legacy systems before designing a replacement. Feature mapping was a crucial step in ensuring that we maintained the essential functionalities users relied on, while simplifying and modernizing the user experience. I learned how vital it is to balance the needs of legacy users with the demands for innovation and usability. The time spent wireframing, prototyping and testing was particularly valuable, as it allowed us to refine complex workflows and avoid costly development changes down the line.
Additionally, I gained a deeper appreciation for the need to engage with a diverse group of users across different teams. Understanding their varying workflows and customizations helped shape a tool that worked across the company, not just for a single group.
What I would improve:
Looking back, I would have requested more assistance in the user research and analysis stage. Handling such a complex project as the sole designer meant there was a significant amount of information to process, and having additional support could've provided even more nuanced insights and faster iterations.