Case Study 02
Contextual Driving Speed Adoption
Contextualizing telemetry to unlock margin in a safe-driving model.
- Role
- Sr. Product Manager
- Year
- 2024
- Team
- PM, data science, data partnerships
- Focus
- Telemetry · ML
Problem Definition
The posted speed limit is not always the safe driving speed. We used speed as one telemetry input to Quanata’s safe driving model, and knew we were leaving margin on the table due to a misaligned metric.
Research & Discovery
In consultation with a data scientist and our data partnerships manager, I investigated alternative data sources to contextualize our telemetry signals from customers. We found a source that provides speed of traffic estimates at good resolution for most of the US.
Strategic Solution
Collaborating with a data scientist, we modeled multiple ways of incorporating contextual speed data into our safe driving model, and settled on a system where we use contextual when certain, and posted when contextual reports ambiguity about which road a driver is on (i.e. access road vs freeway).
Execution & Prioritization
Through the normal quarterly roadmapping process, I earned executive sponsorship for the product increment, focusing on leveraging existing data engineering pipelines, data broker relationships, and strong reach of a change to our core safe driving model.
Impact & Metrics
About $8,000,000 per year in additional margin across our small customer base of ~75,000.