Real-world user context
Requirements had to reflect how enthusiasts prepare for, drive, and review a session at a circuit.
Anonymous motorsports case study
Turning racetrack data into actionable lap insights
A digital product company wanted to turn the raw experience of a track session into useful feedback through a mobile application that combined video, location, telemetry, and performance analysis.
The situation
The product had to translate a fast, physical experience into data people could understand and use.
The client envisioned a data tracker and logger for track enthusiasts, with preloaded circuit profiles, video capture, and visual telemetry analysis at the center of the experience.
Getting the calculations right was only part of the challenge. The application also needed a sleek, usable interface that made complex session information meaningful during review and comparison.
The product challenge
Combine field context, sensor signals, and visual analysis in one mobile product.
The team needed a shared understanding of track-day behavior before shaping the data model, architecture, and review experience.
Multiple synchronized signals
Video, location, speed, acceleration, G-force, and slope needed to become one coherent session record.
Insight, not data overload
Prediction, graphs, vehicle profiles, and comparisons had to help users interpret performance instead of simply displaying raw values.
The solution
Field discovery informed an Agile product architecture for telemetry capture, analysis, and review.
The product lead visited circuits with the client to understand expectations, then coordinated onshore support and offshore development around a shared framework and modular application architecture.
- 01
Learn at the track
Observe the environment and user journey directly before locking down product behavior.
- 02
Build a telemetry framework
Organize circuit profiles, video, sensor calculations, vehicle profiles, and session data as connected modules.
- 03
Review through working demos
Use weekly demonstrations to collect feedback, define the next sprint, and keep distributed contributors aligned.
How we worked
Keep product decisions close to users and delivery decisions visible to the full team.
Field visits grounded the application in real track-day expectations instead of assumptions made at a desk.
A local project lead also served as business analyst, translating product intent and coordinating the distributed development team.
Weekly demos, feedback, and sprint planning gave every developer visibility into the product goal and responsibility for quality.
01Observe
Study track-day behavior and expectations.
02Frame
Define the architecture and core modules.
03Demonstrate
Review working software each week.
04Refine
Use feedback to shape the next sprint.
The result
The delivered mobile app turned track sessions into visual telemetry and comparable performance records.
The application combined circuit profiles, video logging, speed, acceleration, G-force, slope, predictive lap timing, dynamic vehicle profiles, and session summaries with graphs and location views.
Multi-signal telemetryfrom video, location, and motion data
Predictive timingto support lap-by-lap review
Session comparisonacross profiles and performance history
A complete session record
Video and telemetry were brought together so users could revisit both what happened and how the vehicle behaved.
Analysis designed for action
Prediction, graphs, and summaries helped translate measurements into understandable performance feedback.
Shared learning across sessions
The product supported comparing and sharing results without tying the experience to a single isolated run.
Case taxonomy
Searchable by industry, technology, product, and business need.
Industry and product
- Motorsports
- Mobile Application
- Track-day Technology
- Telemetry
Technology and delivery
- Location Data
- Video Capture
- Telemetry Algorithms
- Agile
- Cross-border Delivery
Business need
- Performance Analytics
- Predictive Lap Timing
- G-force Analysis
- Session Comparison
- UX Research
Make field data useful
Need a mobile product that turns sensor data into an experience people can act on?
Get in touch
Ready to build software that fits your business?
Tell us what you need to build, modernize, automate, or augment with AI. We can start with a focused discussion or a no-risk 1-week trial.
“A fantastic company to work with.” After the initial rapid development project, American Shipping Co. kept two Shinetech developers embedded for nearly four years, supporting internal and external tools and new AI initiatives.
CEO, American Shipping Co. - 5-star Google Review