NATIVE MOBILE & TELEMATICS DESIGN

Translating complex vehicle telematics into an intuitive mobile platform for Europe's leading trailer manufacturer

Reduced fleet downtime by up to 30%
High-fidelity prototype showcase of the beUpToDate app screens
Schmitz Cargobull’s legacy desktop fleet management system was clumsy, overwhelming, and inaccessible on the go. Fleet managers and drivers were missing critical, real-time vehicle data (like sudden temperature drops in refrigerated trailers or tire pressure issues), leading to delayed decisions, safety risks, and operational inefficiencies.

Lead the end-to-end product design (iOS & Android) for a new mobile telematics assistant. My goal was to partner with Product and Engineering to translate massive amounts of live vehicle data into a simplified, task-critical mobile workflow that drivers and operators could rely on in fast-paced, field environments.

10-week MVP delivery (followed by 15 months of continuous feature scaling & dev support)

  • Native mobile UX/UI design (iOS HIG & Android Material)
  • Translating massive telematics datasets into intuitive, low-cognitive-load interfaces
  • Cross-functional collaboration (PMs, BAs, and Swift/Kotlin developers)
  • Resourceful usability testing and friction analysis
  • Design system utilization and scalable engineering handoff
  • Achieved a 5-star rating on both App Store & Google Play (1,828 downloads in first 8 months)
  • Improved incident response efficiency by ~50% through real-time mobile notifications
  • Reduced trailer downtime by 15-30% and fuel consumption by 3-10%
  • Successfully adopted across 100,000+ telematics units processing live vehicle data
Real-world user alongside business achievements
Real-world user alongside business achievements

OVERVIEW OF MY DESIGN PROCESS

Step 1 - Empathizing with drivers and fleet operators:

I analyzed the current desktop platform and interviewed the client's fleet coordinators. We uncovered 3 core insights: the existing data was too slow to access, operators lacked out-of-office visibility, and drivers needed vital safety/status notifications without excessive interruption while on the road.

3 main interview insights sticky notes

Step 2 - Information architecture & rapid ideation:

I facilitated the transition from a complex, data-heavy desktop view to a focused mobile architecture. I created low-fidelity wireframes mapped to specific user goals: real-time trailer status, on-the-go control actions, and vital safety alerts.

Low-fidelity sketches and architecture mapping
Low-fidelity sketches and architecture mapping

Step 3 - High-fidelity prototyping for native platforms:

I designed parallel experiences for native iOS and Android. A core focus was simplifying the cognitive load - ensuring that complex telematics (like multi-zone temperature monitoring and engine diagnostics) were scannable at a glance. I built interactive prototypes to align C-suite stakeholders and the product team.

Low-fidelity sketches and architecture mapping
Low-fidelity sketches and architecture mapping

Step 4 - Resourceful "corridor" usability testing:

Operating without a dedicated budget for external user testing, I embraced a "deliver with urgency" mindset. I conducted guerilla corridor tests with internal employees unfamiliar with the project. This friction analysis revealed a critical flaw: vital temperature data was hidden behind clicks. I immediately redesigned the list view to surface this telematics data upfront, vastly improving scannability.

Low-fidelity sketches and architecture mapping

Step 5 - Deep engineering collaboration & agile handoff:

To ensure we hit our aggressive 10-week MVP launch, I worked in tight daily syncs with the iOS and Android developers. I utilized a scalable design system and Zeplin for seamless handoff, ensuring components aligned with native Swift and Kotlin capabilities without compromising the user experience.

Low-fidelity sketches and architecture mapping
By reducing cognitive load and focusing on actionable telematics data, I designed a mobile experience that transformed manual, reactive fleet monitoring into a proactive, real-time workflow.