When MediaMath sought to redefine the user experience for their Demand-Side Platform (DSP)., they turned to Thoughtworks for expertise in crafting a modern, user-centric solution. Among the critical areas identified for improvement was the targeting vertical, encompassing key functionalities like audiences, contextual targeting, location, and technology.
The Team and My Role
The Thoughtworks design team consisted of three senior designers, supported by a tech lead and a robust group of over ten engineers. From MediaMath, a Vice President of UX provided strategic oversight and alignment.
I took on the role of Senior Product Designer for the Location Targeting module, where I was solely responsible for its complete end-to-end redesign. The redesign began with a design sprint with the team, setting the foundation for the vision and direction of the project.
Previous Design:
Redesign:
Context and Problem
MediaMath’s DSP caters to digital marketers managing complex, large-scale advertising campaigns across various industries, with the platform handling over $500 million in advertising spend annually during the time I was working there. These users are detail-oriented, working under tight deadlines to optimize campaign performance.
While the platform offered powerful targeting options, the Location Targeting module had several usability challenges:
Heavy reliance on CSV uploads: Although the old system had a location list and selection preference, users heavily relied on CSV uploads due to the inefficiencies and limited flexibility of the manual selection process.
No support for reusable postal codes: Marketers frequently re-entered commonly used postal codes, as there was no option to save and reuse them.
Unclear forecasting: Key metrics such as impressions, media spend, and CPM were scattered across different sections, making it difficult to evaluate targeting decisions.
Lack of visual and organizational clarity: The summary panel lacked categorization and progress indicators, leaving users unsure if their configurations were complete or accurate.
These issues created frustration, particularly for users managing highly complex campaigns, reducing efficiency and confidence in the platform.
How we did this? --> Google Design Sprint: Process Overview
Our five-day sprint followed a structured approach to redesign the Targeting module, focusing on user needs and rapid iteration. Key activities included:
Customer Journey Mapping to identify pain points in the current workflow.
Crazy Eights and Storyboarding to generate and refine solution ideas.
Competitor Analysis for inspiration and best practices.
Prototyping high-fidelity interfaces with features like presaved postal codes and a forecasting dashboard.
Usability Testing with real users to validate the designs and gather feedback.
This process ensured our solutions were user-centered and actionable.
After completing the sprint, we presented the redesign to key stakeholders, including the VP of Product and VP of UX. Following their approval, we continued refining the design through iterative feedback cycles to ensure it aligned with both user needs and business goals.
Key Contributions
As the designer for the Location Targeting module, some of my key contributions include:
Expanded Screen Space for Search and CSV Management: The new design features integrated accordions for the Search and Postal Code Upload sections, enabling users to collapse or expand each section as needed. This approach allows users to focus on one task at a time, minimizing distractions. By dedicating more screen space to active sections, such as CSV uploads, users can now easily upload, preview, and validate location data directly within the interface, improving both efficiency and accuracy.
Presaved Postal Codes: Designed a feature enabling users to reuse frequently used postal code lists, reducing repetitive tasks.
Interactive Map Preview: Users can now preview their targeting areas on an interactive map, ensuring real-time validation of location choices—a feature missing in the old design.
Dynamic Forecast Dashboard: Developed a real-time panel displaying impressions, CPM, and spend dynamically as users configured their targeting.
Categorized Summaries with Visual Feedback: Organized the summary into clear categories (Audiences, Contextual, and Location) with visual indicators (e.g., checkmarks) to signal completion.
Streamlined location targeting interface with collapsible sections for search and CSV uploads, plus real-time forecasting feedback.
Postal code targeting section expanded, showcasing pre-saved templates, CSV upload options, and real-time forecasting metrics.
Expanded postal code section with map preview, enabling users to upload, visualize, and validate location data directly within the interface
Impact of the Redesign
Although I left the project before the implementation phase was fully completed, the feedback during usability testing and from initial rollouts was overwhelmingly positive:
User Enthusiasm: Users praised the intuitive workflows and real-time forecasting features during testing, with many expressing how the changes would significantly improve their efficiency.
Pre-Implementation Surveys: 87% out of 20 testers rated the redesigned Location Targeting module as “intuitive and efficient.”
Feedback from the MediaMath Team: After my departure, I heard from the team that users were particularly excited about the presaved postal codes and forecasting dashboard, which addressed two of the most common pain points.
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