Track Side Data
Simplified
Track Side
Data
Simplified
Pitline | End-to-End Mobile App
Pitline | End-to-End Mobile App
Problem
Inconsistent data leads to missed performance.
Inconsistent data leads to missed performance.
Grassroots racers rely on scattered tools that fail to capture setups and weather. This fragmented data adds stress and limits improvement. 7 of 8 racers in interviews reported losing critical notes during a weekend.
Grassroots racers rely on scattered tools that fail to capture setups and weather. This fragmented data adds stress and limits improvement. 7 of 8 racers in interviews reported losing critical notes during a weekend.
Notes get lost → 62% admitted losing setup notes in the paddock
Spreadsheets → average update time: 5–10 minutes per session
Lap timers lack context → 100% used them, but none tied laps to setups or weather
Fragmented records → 7 of 8 racers couldn’t identify patterns over a season
Notes get lost → 62% admitted losing setup notes in the paddock
Spreadsheets → average update time: 5–10 minutes per session
Lap timers lack context → 100% used them, but none tied laps to setups or weather
Fragmented records → 7 of 8 racers couldn’t identify patterns over a season
Solution
A lightweight race-day logging tool for confident decisions.
A lightweight race-day logging tool for confident decisions.
Pitline brings setups, weather, and lap times into one paddock-ready app. This streamlined flow reduces stress and builds confidence. In usability tests, all racers completed tasks with ease and preferred Pitline over their current methods.
Pitline brings setups, weather, and lap times into one paddock-ready app. This streamlined flow reduces stress and builds confidence. In usability tests, all racers completed tasks with ease and preferred Pitline over their current methods.
Quick logging → reduced entry time from 8–10 min to <2 min
Centralized records → 100% of testers could retrieve past sessions instantly
Linked insights → 5 of 6 testers valued connecting weather to performance
Actionable data → 100% of testers felt more confident making trackside setup changes
Quick logging → reduced entry time from 8–10 min to <2 min
Centralized records → 100% of testers could retrieve past sessions instantly
Linked insights → 5 of 6 testers valued connecting weather to performance
Actionable data → 100% of testers felt more confident making trackside setup changes
Why Grassroots Racing?
Why Grassroots Racing?
Why Grassroots Racing?
The idea began in the custom Toyota shop where I work. Nick, the owner and founder of Nixspeed Customs, competes in Global Time Attack events and mentioned he wished he had a better way to track setups, weather, and lap data. When he learned I was in a UX bootcamp, he suggested building a tracker — the spark that grew into my real client study.
The idea began in the custom Toyota shop where I work. Nick, the owner and founder of Nixspeed Customs, competes in Global Time Attack events and mentioned he wished he had a better way to track setups, weather, and lap data. When he learned I was in a UX bootcamp, he suggested building a tracker — the spark that grew into my real client study.
Role
Role
End-to End UX Researcher & UI Designer
End-to End UX Researcher & UI Designer
Team
Team
Solo
Solo
Timeline
Timeline
4 Weeks
4 Weeks
Type
Type
Real Client
Real Client
Tools
Tools
Figma, FigJam, Figma Make, Fireflies.ai, ChatGPT
Figma, FigJam, Figma Make, Fireflies.ai, ChatGPT
Empathize
Empathize
Racers Prioritize Tires and Weather Above All
Racers Prioritize Tires and Weather Above All
User Interview
Competitive Analysis
Affinity Mapping
Naturalistic Observation
To understand the realities of grassroots racing, I went beyond the tools and into the paddock itself. A competitive scan of popular apps like RaceChrono, TrackAddict, and Harry’s LapTimer revealed a blind spot: they tracked laps well, but left setups and weather out of the equation, and most did offer an easy option for manual tracking. Trackside observation with Global Time Attack drivers brought that gap to life. I watched them scrambling to log tire pressures before the temps cooled, juggling quick setup tweaks, and scribbling scattered notes before the next session.
To dig deeper, I ran eight in-person interviews, recorded and transcribed with Fireflies.ai, using a semi-structured guide around behaviors, pain points, and goals.
To understand the realities of grassroots racing, I went beyond the tools and into the paddock itself. A competitive scan of popular apps like RaceChrono, TrackAddict, and Harry’s LapTimer revealed a blind spot: they tracked laps well, but left setups and weather out of the equation, and most did offer an easy option for manual tracking. Trackside observation with Global Time Attack drivers brought that gap to life. I watched them scrambling to log tire pressures before the temps cooled, juggling quick setup tweaks, and scribbling scattered notes before the next session.
To dig deeper, I ran eight in-person interviews, recorded and transcribed with Fireflies.ai, using a semi-structured guide around behaviors, pain points, and goals.
Behaviors
Behaviors
Example Question
“Walk me through how you currently track setups, weather and lap data?”
“Walk me through how you currently track setups, weather and lap data?”
“Which tools or notes do you rely on most during the paddock rush?”
“Which tools or notes do you rely on most during the paddock rush?”
Pain Points
Pain Points
Example Question
“What’s the biggest challenge when trying to understand how conditions affect your performance?”
“What’s the biggest challenge when trying to understand how conditions affect your performance?”
“When have you lost or missed critical notes?”
“When have you lost or missed critical notes?”
Goals
Goals
Example Question
“What would make it easier to connect setups with performance?”
“What would make it easier to connect setups with performance?”
“If you could design your ideal tool, what would it do?”
“If you could design your ideal tool, what would it do?”
A few driving questions from my user interviews.
A few driving questions from my user interviews.
Pulling these threads together through affinity mapping, two truths stood out clearly: tires and weather drive the majority of race-day decisions, and any workflow that isn’t fast and simple simply won’t survive in the paddock.
Pulling these threads together through affinity mapping, two truths stood out clearly: tires and weather drive the majority of race-day decisions, and any workflow that isn’t fast and simple simply won’t survive in the paddock.
View the full Affinity Map here.
View the full Affinity Map here.
Affinity Map Snippet
Affinity Map Snippet
What I Found
Scattered tools left racers stressed and unprepared.
Scattered tools left racers stressed and unprepared.
Apps captured laps but ignored setups/weather
Spreadsheets 5–10 min per update, slowing paddock workflows
Paper notes were easy in the moment, useless later
Fragmented systems → all 8 racers voiced frustration with juggling tools
Apps captured laps but ignored setups/weather
Spreadsheets 5–10 min per update, slowing paddock workflows
Paper notes were easy in the moment, useless later
Fragmented systems → all 8 racers voiced frustration with juggling tools
Key Insight
Tires and weather decide the race, time pressure shapes the workflow.
Tires and weather decide the race, time pressure shapes the workflow.
Tires & weather are the #1 factors in every driver’s decisions
Performance link: racers lacked a way to tie setups to outcomes
Short windows for post data logging made multi-step tools unrealistic
Need → a simple, unified system racers could rely on trackside
Tires & weather are the #1 factors in every driver’s decisions
Performance link: racers lacked a way to tie setups to outcomes
Short windows for post data logging made multi-step tools unrealistic
Need → a simple, unified system racers could rely on trackside
Define
Define
Design Must Mirror the Race-Day Routine
Design Must Mirror the Race-Day Routine
POV
HMW
Project Goals
Personas
Problem Statement
After synthesizing research, one theme kept surfacing: tires and weather drive performance, yet racers had no reliable way to capture them quickly in the paddock. The result was scattered notes, partial app data, and lost opportunities to learn.
This led to a clear point of view: Time Attack drivers chasing personal bests and class records need a unified, trackside tool that makes logging tires and weather as simple as timing a lap.
From that perspective, the design challenge sharpened into a single question:
After synthesizing research, one theme kept surfacing: tires and weather drive performance, yet racers had no reliable way to capture them quickly in the paddock. The result was scattered notes, partial app data, and lost opportunities to learn.
This led to a clear point of view: Time Attack drivers chasing personal bests and class records need a unified, trackside tool that makes logging tires and weather as simple as timing a lap.
From that perspective, the design challenge sharpened into a single question:
How Might We centralize tire, weather, and setup data in one intuitive platform so drivers can make consistent, data-driven adjustments between sessions?
How Might We centralize tire, weather, and setup data in one intuitive platform so drivers can make consistent, data-driven adjustments between sessions?
From this question, I defined project goals that would guide Pitline’s direction. The focus was on creating a tool that racers would actually use under paddock pressure — lightweight enough to be quick, precise enough to be trusted, and actionable enough to improve performance over time. These goals served as the foundation for design decisions.
From this question, I defined project goals that would guide Pitline’s direction. The focus was on creating a tool that racers would actually use under paddock pressure — lightweight enough to be quick, precise enough to be trusted, and actionable enough to improve performance over time. These goals served as the foundation for design decisions.
Project Goals Venn Diagram
Project Goals Venn Diagram
Personas
To ensure the solution stayed grounded in research, I synthesized findings from interviews, trackside observation, and affinity mapping into two personas. These personas captured the spectrum of racer behaviors and motivations that emerged:
Alex, the Data-Driven Driver meticulous and data-hungry, reflecting participants who wanted precise, comparable records.
Jay, the Weekend Racer casual but committed, echoing those who valued improvement but resisted complex tools.
Personas
To ensure the solution stayed grounded in research, I synthesized findings from interviews, trackside observation, and affinity mapping into two personas. These personas captured the spectrum of racer behaviors and motivations that emerged:
Alex, the Data-Driven Driver meticulous and data-hungry, reflecting participants who wanted precise, comparable records.
Jay, the Weekend Racer casual but committed, echoing those who valued improvement but resisted complex tools.
Define
Define
Design Must Mirror the Race-Day Routine
Design Must Mirror the Race-Day Routine
POV
HMW
Project Goals
Personas
Problem Statement
Personas
Personas
Together, these personas highlighted a shared pain point that framed the problem Pitline set out to solve.
Together, these personas highlighted a shared pain point that framed the problem Pitline set out to solve.
Problem Statement
Global Time attack racers struggle to track weather, tire pressures, and lap data with fragmented tools or paper notes. They need one intuitive tool that consolidates key metrics, integrates weather data, and delivers actionable insights without unnecessary complexity.
Problem Statement
Global Time attack racers struggle to track weather, tire pressures, and lap data with fragmented tools or paper notes. They need one intuitive tool that consolidates key metrics, integrates weather data, and delivers actionable insights without unnecessary complexity.
Ideate
Ideate
Start Simple, Grow with Precision
Start Simple, Grow with Precision
User Flow
Task Flow
Feature Set
Prompt Generation
Lo-Fi Prototype
User Test
With Alex and Jay as anchors, I started by mapping the big picture through user flows. These showed the full race-day journey — pre-session prep, in-session logging, and post-session review — including decision points like whether to:
Adjust setups now or wait
Capture full tire temps or just pressures
Skip notes altogether if time was too tight
From there, I distilled the essentials into task flows. These stripped away the branches and captured the happy path:
Start a session
Log conditions
Record results
Together, the flows kept Pitline honest to paddock reality — broad enough to reflect the chaos, simple enough to streamline the core routine.
With Alex and Jay as anchors, I started by mapping the big picture through user flows. These showed the full race-day journey — pre-session prep, in-session logging, and post-session review — including decision points like whether to:
Adjust setups now or wait
Capture full tire temps or just pressures
Skip notes altogether if time was too tight
From there, I distilled the essentials into task flows. These stripped away the branches and captured the happy path:
Start a session
Log conditions
Record results
Together, the flows kept Pitline honest to paddock reality — broad enough to reflect the chaos, simple enough to streamline the core routine.
Task Flows & User Flows
Task Flows & User Flows
With racer needs and goals defined, I explored how Pitline could take shape by building a prioritized feature set list. This separated essentials for the MVP from long-term opportunities:
P0 – Must Have → user profiles, lap data logging, weather snapshots
P1 – Should Have → predictive insights, community sharing
P2 – Nice to Have → analytics dashboards, sensor integrations
To bring these priorities into focus, I highlighted the core features Pitline needed on day one and framed how the product could grow beyond the MVP. The essentials addressed racers’ biggest frustrations: quick ways to log laps, track weather, and save setups. Future opportunities pointed toward richer insights, community connection, and advanced integrations.
With racer needs and goals defined, I explored how Pitline could take shape by building a prioritized feature set list. This separated essentials for the MVP from long-term opportunities:
P0 – Must Have → user profiles, lap data logging, weather snapshots
P1 – Should Have → predictive insights, community sharing
P2 – Nice to Have → analytics dashboards, sensor integrations
To bring these priorities into focus, I highlighted the core features Pitline needed on day one and framed how the product could grow beyond the MVP. The essentials addressed racers’ biggest frustrations: quick ways to log laps, track weather, and save setups. Future opportunities pointed toward richer insights, community connection, and advanced integrations.
P1 | Must Have
Tire Logging
Tire Logging
Quickly record pressures and temps before and after each session.
Quickly record pressures and temps before and after each session.
User Story: As Alex, when I use Pitline, I want to log my tire pressures and temps trackside so I can see how they affect lap performance and setup decisions.
User Story: As Alex, when I use Pitline, I want to log my tire pressures and temps trackside so I can see how they affect lap performance and setup decisions.
P1 | Must Have
Weather Snapshots
Weather Snapshots
Capture changing conditions like temperature, humidity, and cloud cover without extra tools.
Capture changing conditions like temperature, humidity, and cloud cover without extra tools.
User Story: As Jay, when I use Pitline, I want to log weather conditions in seconds so I can understand how the track is changing without slowing down my prep.
User Story: As Jay, when I use Pitline, I want to log weather conditions in seconds so I can understand how the track is changing without slowing down my prep.
P1 | Must Have
Setup Tracking
Setup Tracking
Log suspension, aero, and other car setup changes alongside each session.
Log suspension, aero, and other car setup changes alongside each session.
User Story: As Alex, when I use Pitline, I want to tie setup adjustments to lap data so I can see what’s actually improving performance.
User Story: As Alex, when I use Pitline, I want to tie setup adjustments to lap data so I can see what’s actually improving performance.
P1 | Must Have
Session Summaries
Session Summaries
Auto-organized records of each run that highlight what was tried and what worked.
Auto-organized records of each run that highlight what was tried and what worked.
User Story: As Jay, when I use Pitline, I want a simple summary of my sessions so I can review progress without sorting through scattered notes.
User Story: As Jay, when I use Pitline, I want a simple summary of my sessions so I can review progress without sorting through scattered notes.
MVP List
MVP List
Low-Fi Wireframe Exploration with AI
After synthesizing my interviews, I built a prioritized list of what racers needed to track pre- and post-session. To quickly validate those flows, I turned insights into screen prompts and generated wireframes with Figma Make.
Testing with 4 drivers confirmed the pre/post-session flow and tire placement worked as intended, while feedback revealed a need for clearer labels and more flexible handling inputs.
Low-Fi Wireframe Exploration with AI
After synthesizing my interviews, I built a prioritized list of what racers needed to track pre- and post-session. To quickly validate those flows, I turned insights into screen prompts and generated wireframes with Figma Make.
Testing with 4 drivers confirmed the pre/post-session flow and tire placement worked as intended, while feedback revealed a need for clearer labels and more flexible handling inputs.
View the Prototype and Prompting in Figma Make here.
View the Prototype and Prompting in Figma Make here.
Lo-Fi Prototype
Lo-Fi Prototype
What I Found
Early AI-generated wireframes validated Pitline’s core flows.
Early AI-generated wireframes validated Pitline’s core flows.
Tire tracking flowed well placement of pressures/temps post-session matched natural routines
Summary screen added value drivers wanted before/after pressures & setup notes for peer sharing
Terminology worked, mostly labels like “tire wear” and “handling” felt clear, but suspension/aero inputs lacked precision
Tire tracking flowed well placement of pressures/temps post-session matched natural routines
Summary screen added value drivers wanted before/after pressures & setup notes for peer sharing
Terminology worked, mostly labels like “tire wear” and “handling” felt clear, but suspension/aero inputs lacked precision
Key Insight
Drivers wanted precision and flexibility build into simple flows.
Drivers wanted precision and flexibility build into simple flows.
Quantitative inputs needed suspension, aero, and ride height must allow numbers, not vague dropdowns
Smarter defaults fuel and weight should auto-carry from past sessions
Optional notes matter context like “oversteer on shallow turn” adds nuance
Quantitative inputs needed suspension, aero, and ride height must allow numbers, not vague dropdowns
Smarter defaults fuel and weight should auto-carry from past sessions
Optional notes matter context like “oversteer on shallow turn” adds nuance
Branding
Drivers Need Clarity, Precision, and Flexibility
Drivers Need Clarity, Precision, and Flexibility
Style Tile
Component Library
Hi-Fi Design
Branding
With the structure validated, I moved into high-fidelity design. To keep Pitline grounded in racing culture, I drew inspiration directly from Nick’s MR2 racecar. Its bold lines, retro decals, and gritty paddock energy. I translated that into a moodboard and style tile, shaping a visual system that feels track-inspired, bold, and unmistakably built for racers.
Branding
With the structure validated, I moved into high-fidelity design. To keep Pitline grounded in racing culture, I drew inspiration directly from Nick’s MR2 racecar. Its bold lines, retro decals, and gritty paddock energy. I translated that into a moodboard and style tile, shaping a visual system that feels track-inspired, bold, and unmistakably built for racers.
Style Tile
Style Tile
Hi-Fidelity Design
User feedback directly shaped key design decisions, ensuring Pitline stayed true to racer needs:
Replaced vague sliders with precise quantitative inputs (click counts for shocks, hole positions for wings).
Added tooltips to guide technical fields like ride height.
Designed expandable notes fields so drivers could capture nuance in handling feedback.
I built components as I iterated, then finalized the UI kit at the end to guarantee consistency across typography, color, and reusable elements.
Hi-Fidelity Design
User feedback directly shaped key design decisions, ensuring Pitline stayed true to racer needs:
Replaced vague sliders with precise quantitative inputs (click counts for shocks, hole positions for wings).
Added tooltips to guide technical fields like ride height.
Designed expandable notes fields so drivers could capture nuance in handling feedback.
I built components as I iterated, then finalized the UI kit at the end to guarantee consistency across typography, color, and reusable elements.
Final Hi-Fi Prototype Screens
Final Hi-Fi Prototype Screens
Test
Drivers Highlighted Clarity and Precision Gaps
Drivers Highlighted Clarity and Precision Gaps
Hi-Fi Prototype
Usability Test
Iteration
I ran moderated usability tests with three Global Time Attack drivers to validate Pitline in real paddock conditions. The core flows were rated highly, and all participants confirmed they would use Pitline over their current methods. Feedback guided immediate refinements while also highlighting opportunities for future iterations.
I ran moderated usability tests with three Global Time Attack drivers to validate Pitline in real paddock conditions. The core flows were rated highly, and all participants confirmed they would use Pitline over their current methods. Feedback guided immediate refinements while also highlighting opportunities for future iterations.
What I Found
Useability testing surfaced areas for refinement.
Useability testing surfaced areas for refinement.
Terminology confusion → “Continue Session” felt unclear
Summary buried → extended session details weren’t visible enough
Workflow gaps → no quick way to start a new session from the summary screen
Limited flexibility → track temperature couldn’t be edited once logged
Terminology confusion → “Continue Session” felt unclear
Summary buried → extended session details weren’t visible enough
Workflow gaps → no quick way to start a new session from the summary screen
Limited flexibility → track temperature couldn’t be edited once logged
Key Insight
Maximize clarity and speed in the paddock.
Maximize clarity and speed in the paddock.
Clearer labels → renamed “Continue Session” to “Post-Session”
Faster turnaround → added “Start New Session” CTA on summary screen
Better visibility → promoted extended summary into its own page
Future focus → visuals, wear scales, and predictive setup suggestions deferred to later releases
Clearer labels → renamed “Continue Session” to “Post-Session”
Faster turnaround → added “Start New Session” CTA on summary screen
Better visibility → promoted extended summary into its own page
Future focus → visuals, wear scales, and predictive setup suggestions deferred to later releases
Why This Balance
I prioritized updates that improve clarity and speed in live sessions, deferring personalization features to future iterations since they don’t block usability today.
Why This Balance
I prioritized updates that improve clarity and speed in live sessions, deferring personalization features to future iterations since they don’t block usability today.
Feedback Edits
Feedback Edits
Final Design & Next Steps
Actionable Insights Without Complexity
Actionable Insights Without Complexity
Iteration
Reflection
Usability testing validated Pitline’s core flows, while refinements improved clarity and speed. The result was a product that balanced depth for advanced racers with simplicity for casual drivers, and set a strong foundation for consistent design moving forward.
Usability testing validated Pitline’s core flows, while refinements improved clarity and speed. The result was a product that balanced depth for advanced racers with simplicity for casual drivers, and set a strong foundation for consistent design moving forward.
Key Outcomes
Depth for advanced drivers, simplicity for weekend drivers.
Depth for advanced drivers, simplicity for weekend drivers.
Racer feedback is gold → conversations shaped both features and workflow
Time pressure defines design → short windows between sessions drove every decision
Balance matters → depth for advanced racers, simplicity for weekend drivers
Racer feedback is gold → conversations shaped both features and workflow
Time pressure defines design → short windows between sessions drove every decision
Balance matters → depth for advanced racers, simplicity for weekend drivers
Next Steps
What's in store for Pitline's future in the paddock.
What's in store for Pitline's future in the paddock.
Expand flows → add user profiles, car profiles, and track management
Test at scale → run broader usability studies with varying experience levels
Private beta → explore no-code launch with shop drivers to validate in live use
Expand flows → add user profiles, car profiles, and track management
Test at scale → run broader usability studies with varying experience levels
Private beta → explore no-code launch with shop drivers to validate in live use
Final Screens
Final Screens
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2025 Stevie Nichole Morris
2025 Stevie N Morris