FleetSync

From Data to Decisions

My role

Product designer

Launched

10 month

Company & Product Context

FleetSync builds operational software for transportation providers managing large commercial fleets across Europe. The platform helps operations teams monitor vehicle location, trip progress, driver activity, and operational exceptions through a centralized web application. As FleetSync scaled to support larger customers, the product evolved toward replacing fragmented internal tools with a single, unified operational system. The Operations Dashboard became the primary interface used daily by dispatchers to coordinate vehicles and communicate with drivers in real time.

Role

Lead Designer

Scope

End-to-end UX strategy and design across discovery, concept and launch

Business Impact

Drove alignment on multi-year vision and product direction

User Impact

446K+ users, 950K+ pins, 45% repeat usage, 56% engagement

Company & Product Context

Role

Lead Designer

Scope

End-to-end UX strategy and design across discovery, concept and launch

Business Impact

Drove alignment on multi-year vision and product direction

User Impact

446K+ users, 950K+ pins, 45% repeat usage, 56% engagement

Deep Dive

The problem

As FleetSync onboarded larger fleets, the Operations Dashboard struggled to support increasing operational complexity. Dispatchers needed to monitor more vehicles, react to more exceptions, and coordinate more drivers, all while switching between multiple screens and external tools. Critical information was fragmented across tabs, making it difficult to maintain situational awareness during peak hours.

Referencing required leaving the reading experience entirely

What I uncovered

Referencing saved content required 6+ disconnected steps, forcing readers to exit the reading experience and navigate across multiple surfaces.

These workflows were not only inefficient, they directly conflicted with how people actually read.

Readers weren’t moving linearly. They were:

Revisiting earlier sections
Comparing ideas across pages
Referencing diagrams and key passages in real time

…Yet Kindle’s model treated referencing as something to do after reading, not during it.

Critical insight

Even when exploring improvements to existing tools, the underlying model remained unchanged.

Content was treated as something to save and retrieve later, rather than something to use in context, alongside the reading experience.

This created a fundamental gap between:

How content was structured in the product
How readers actually needed to interact with it

The real problem

This reframed the problem entirely.

Rather than improving highlights, notes, or bookmarks, the opportunity was to rethink how referencing worked at a system level.

This led to the introduction of a new concept:

Pinnable Content: Enabling readers to surface and interact with content directly within the page, without leaving their reading flow.

This direction gained traction as a high impact opportunity, informing both design exploration and product investment for the team.

The problem

Referencing required leaving the reading experience entirely

What I uncovered

Revisiting earlier sections
Comparing ideas across pages
Referencing diagrams and key passages in real time

…Yet Kindle’s model treated referencing as something to do after reading, not during it.

Critical insight

Even when exploring improvements to existing tools, the underlying model remained unchanged.

Content was treated as something to save and retrieve later, rather than something to use in context, alongside the reading experience.

This created a fundamental gap between:

How content was structured in the product
How readers actually needed to interact with it

The real problem

This reframed the problem entirely.

Rather than improving highlights, notes, or bookmarks, the opportunity was to rethink how referencing worked at a system level.

This led to the introduction of a new concept:

Pinnable Content: Enabling readers to surface and interact with content directly within the page, without leaving their reading flow.

This direction gained traction as a high impact opportunity, informing both design exploration and product investment for the team.

How might we

How might we enable readers to reference content in context, without disrupting their reading flow?

Research

Research methods

Behavioral analysis of reading and annotation patterns

Competitive analysis

Customer interviews and surveys to uncover pain points

Usability testing (two rounds)

Customer surveys

Cross-functional workshops to align on gaps and opportunities

Research methods

Behavioral analysis of reading and annotation patterns

Competitive analysis

Customer interviews and surveys to uncover pain points

Usability testing (two rounds)

Customer surveys

Cross-functional workshops to align on gaps and opportunities

Understanding the Opportunity Space

To explore how referencing could better support reading, I led a discovery phase spanning competitive analysis, behavioral research, and iterative user testing.

Rather than optimizing existing tools, the goal was to understand how referencing should work within a digital reading experience.

What we explored

I analyzed patterns across adjacent products—including Apple Books, Notion, Google Docs, and media platforms like Netflix and Apple TV—to understand how primary content and supporting tools coexist.

This revealed two key tensions:

PiP patterns worked well for passive consumption, where content is viewed at a glance
Interactive tools required stability and depth, especially when users needed to read, scroll, or zoom

Additionally, platforms like Notion and Apple Books demonstrated that users are comfortable with on-page tooling—so long as it enhances the primary task rather than distracting from it.

This challenged an existing assumption within Kindle: that preserving a “reading sanctuary” required minimizing all on-page UI.

What we learned from users

Through multiple rounds of user testing, a different pattern emerged.

Users didn’t just want access to saved content—they wanted to interact with it meaningfully.

They prioritized not losing their place in the book
They expected to scroll, zoom, and explore pinned content
They quickly created new workflows (e.g., pinning answers, building flashcards)
They welcomed on-page tools when they added clear utility

Critical insight

Referencing is not a passive behavior—it’s an interactive one.

This invalidated our initial assumption.

We had optimized for visibility (seeing content alongside reading), but users optimized for interaction (engaging with the content itself).

Design implication

This led to a key reframing:

The problem was not how to surface content
It was how to support interaction without disrupting reading

Which required moving beyond existing tool-based models entirely.

Ideation

Validating the interaction model

From floating overlays → integrated reference

Early exploration focused on a Picture-in-Picture (PiP) approach, allowing pinned content to float above the page while users continued reading.

This prioritized flexibility and visibility—but introduced new challenges.

What didn’t work

Floating windows created gesture complexity and cognitive load
Overlapping interactions made it difficult to scroll and engage with content
The model favored glancing, not deeper interaction

Most importantly, it forced users to split attention between:

Reading the page
Interacting with pinned content

What changed

Floating windows created gesture complexity and cognitive load
Overlapping interactions made it difficult to scroll and engage with content
The model favored glancing, not deeper interaction

Most importantly, it forced users to split attention between:

Reading the page
Interacting with pinned content

The pivotal moment

Supporting interaction mattered more than maintaining simultaneous visibility.

→ This marked a turning point in the design direction.

Validating the interaction model

From floating overlays → integrated reference

Early exploration focused on a Picture-in-Picture (PiP) approach, allowing pinned content to float above the page while users continued reading.

This prioritized flexibility and visibility—but introduced new challenges.

What didn’t work

Floating windows created gesture complexity and cognitive load
Overlapping interactions made it difficult to scroll and engage with content
The model favored glancing, not deeper interaction

Most importantly, it forced users to split attention between:

Reading the page
Interacting with pinned content

What changed

Floating windows created gesture complexity and cognitive load
Overlapping interactions made it difficult to scroll and engage with content
The model favored glancing, not deeper interaction

Most importantly, it forced users to split attention between:

Reading the page
Interacting with pinned content

The pivotal moment

Supporting interaction mattered more than maintaining simultaneous visibility.

→ This marked a turning point in the design direction.

Iterations to final design

Improved visibility, increased complexity

Anchored model, but over engineered for MLP

Balanced interaction model (MLP)

Final Experience

Define, Valitation, iterate

We started with low-fidelity wireframes to explore multiple layout directions quickly. Each iteration was reviewed with internal stakeholders before being tested with customers. Feedback was incorporated continuously, allowing us to converge on a solution that balanced operational speed, clarity, and scalability.

Feedback from customers

Ongoing feedback sessions with dispatchers and operations managers helped us validate early assumptions and refine priorities. Customers emphasized the need for clarity over density, and consistency over flexibility. These sessions guided multiple iterations of the concept before moving into validation.

Positive feedbacks

Usage

Most participants reported faster task completion when using the new layout. Reduced navigation steps and clearer information hierarchy helped dispatchers react more quickly during peak operational hours.

Easy to use

Customers perceived the solution as a clear improvement compared to their existing tools. The interface felt more predictable and required less explanation, especially for new team members.

History

Users confirmed that historical data is mainly used for investigations. As a result, it was deprioritized in the primary view and moved to a secondary layer, reducing visual noise in daily operations.

Feedback from customers

Positive feedbacks

Usage

Easy to use

Customers perceived the solution as a clear improvement compared to their existing tools. The interface felt more predictable and required less explanation, especially for new team members.

History

Outcome and impact

Pinnable Content introduced a new model for in context referencing, fundamentally changing how readers interact with information while reading.

Instead of navigating away to manage saved content, readers could engage with it directly, leading to deeper interaction, higher retention and new reading behaviors.

Outcome and impact

Pinnable Content introduced a new model for in context referencing, fundamentally changing how readers interact with information while reading.

Instead of navigating away to manage saved content, readers could engage with it directly, leading to deeper interaction, higher retention and new reading behaviors.

950k+

Pins created

45%

Repeat usage after first pin

56%

Pin interaction rate

What this means

These metrics show that readers didn’t just save content, they actively used it.

Referencing became part of the reading experience, supporting behaviors like studying, comparing ideas, and revisiting key information without breaking flow.

Product impact

Established a new interaction model for in-book experiences
Influenced broader investment in interactive and AI-powered reading features
Helped shift Kindle from linear consumption → active engagement

This work reinforced that meaningful innovation in reading isn’t about adding more features, it’s about rethinking how interaction fits within the experience itself.

Company & Product Context

Company & Product Context

The problem

The problem

How might we

How might we

How might we enable readers to reference content in context, without disrupting their reading flow?

How might we enable readers to reference content in context, without disrupting their reading flow?

Research

Research methods

Research methods

Validating the interaction model

Validating the interaction model

Iterations to final design

Define, Valitation, iterate

Feedback from customers

Positive feedbacks

Usage

Easy to use

History

Feedback from customers

Positive feedbacks

Usage

Easy to use

History

Outcome and impact

Outcome and impact

950k+

Pins created

45%

Repeat usage after first pin

56%

Pin interaction rate

Hear it from our customers..

What I learned from this project