Ad Tracker for Uber
Advertising management platform, internal marketing system for a world wide operating company.
Significantly saves efforts and money allowing marketers to launch, track and manage campaigns and their budget in Facebook, Instagram, Google, Twitter, Linkedin and Apple Search Ads.
Significantly saves efforts and money allowing marketers to launch, track and manage campaigns and their budget in Facebook, Instagram, Google, Twitter, Linkedin and Apple Search Ads.
Problem: Uber's advertising teams were drowning in data across multiple platforms (Meta, Google, Apple, TikTok), spending hours manually monitoring campaigns, and struggling to quickly identify performance issues before they impacted budget efficiency.
My Contribution: UX Designer working with a team of 5 engineers, product manager and data scientist.
Key Achievement: Reduced campaign optimization time by 35% and decreased manual monitoring effort by 60% through role-based dashboard customization.
My Contribution: UX Designer working with a team of 5 engineers, product manager and data scientist.
Key Achievement: Reduced campaign optimization time by 35% and decreased manual monitoring effort by 60% through role-based dashboard customization.
TL;DR
Tracker before our intervention. Nobody used it
Market Context: Legacy tools like Google Ads Manager and Facebook Ads Manager required constant tab-switching and manual data exports.
Target Users:
- Media Analysts (45% of users): Daily campaign monitoring and optimization;
- Campaign Managers (35% of users): Strategic oversight and budget allocation;
- Creative Directors (20% of users): Performance-driven creative optimization.
Business Goal: Uber's advertising division needed to scale efficiently while maintaining tight control over multi-million dollar ad spend across various platforms. The company was experiencing rapid growth in its advertising business, having launched the division in 2019 and reaching *** *** *** in annual revenue.
1 · Context & Constraints
Introduced a side-by-side creatives mode with instant visual and KPI overlay
Solution:
Media buyers struggled to compare ad creatives efficiently – thumbnails hidden, and switching views was slow
Problem:
#4: Creative Comparison
Collaborated with engineering to implement smart caching and progressive loading
Solution:
Real-time data processing limitations affecting dashboard responsiveness
Problem:
#3: Technical Constraints
Implemented progressive disclosure with insight prioritization
Solution:
Initial designs displayed too much information simultaneously, leading to analysis paralysis
Problem:
#2: Data Overwhelm
Created unified customer objects with cross-platform ID tracking
Users struggled to correlate performance across Facebook, Google, and TikTok
Problem:
Solution:
#1: Multi-Platform Complexity
Problems & Solutions:
Design Strategy: Human-centered design approach focused on reducing cognitive load while keeping data richness. The strategy focused on progressive disclosure and role-based customization to serve different user expertise levels.
2 · Design Process
3 · Solution
The Uber Advertising Tracker featured six core innovation areas:
1
Real-Time Anomaly Detection: Plain-language alerts for spend spikes and CTR drops, eliminating the need for constant dashboard monitoring
2
Drag-and-Drop Role-Based Layouts: Customizable widget arrangements with presets for different user types (analyst, executive, creative)
3
Cross-Channel Unified IDs: Server-side tracking that connected user interactions across all advertising platforms
4
Side-by-Side Creative Comparison: Visual thumbnail overlays with KPI comparisons for creative performance analysis
5
Multi-Brand Partitioning: Top-bar switcher for instant data segmentation across Uber's various business units
6
Sandbox Simulation: Safe testing environment for bid changes with rollback capabilities
Campaigns overview
Budget management
A/B testing
Creatives management
Before: Teams spent mornings manually checking 2-4 different platforms, exporting CSV files, and building reports in spreadsheets. Critical issues were often discovered hours or days after they occurred.
After: Teams received intelligent morning briefings with prioritized actions. 89% of campaign issues were identified and addressed within 30 minutes of occurrence.
After: Teams received intelligent morning briefings with prioritized actions. 89% of campaign issues were identified and addressed within 30 minutes of occurrence.
Cross-Team Collaboration
Deparments started using each other's dashboards
Faster decision-making on campaign adjustments
Decision Quality
Scale Efficiency
Enabled team to manage 40% more campaigns without additional headcount
23% increase in advertising ROI through faster optimization cycles
ROI Improvement
Business Impact
What I'd Do Differently:
- Earlier Technical Validation: Would have involved engineering earlier in the ideation phase to understand data processing limitations before designing interactions;
- Broader User Research: Would have included more occasional users to understand different or weird usage patterns;
- Performance Metrics: As an outsourcing team member, I haven't access to Uber metrics, and of course it will be nice to have more granular success metrics around specific user tasks rather than broad efficiency measures.
What Worked Well:
- User-Centered Research: Embedding with advertising teams for a week provided invaluable context about their daily workflows;
- Cross-Functional Collaboration: Working closely with data scientists ensured auto recommendations were actually actionable, not just technically impressive;
- Iterative Testing: prototype testing sessions with real users prevented us from building features that looked fancy but weren't practical in battle;
- Stakeholder Alignment: Regular showcase sessions kept stakeholders invested and provided valuable feedback on strategic direction.
4 · Reflection & Learning
The Uber Advertising Tracker project demonstrated how UX design can transform complex, data-heavy workflows into intuitive experience. By focusing on real user needs, we created a platform that not only solved immediate problems but also scaled to support Uber's growing advertising business.
