Case Study: Lyft achieves scalable privacy reviews with TerraTrue

How Lyft does privacy at scale

The ride-sharing company Lyft faced a significant challenge as its small, two-person privacy team struggled to manage approximately 200 annual reviews using inefficient, manual processes in Google Docs. This system lacked consistency, provided no meaningful metrics, and hindered the team's ability to scale and build deep relationships with product and engineering teams, all while the company was preparing to go public. To address this, Lyft sought a privacy operations management solution from a vendor like TerraTrue that could integrate seamlessly with its existing workflows.

Lyft implemented TerraTrue's platform to automate and streamline its privacy review process. The solution integrated directly with Lyft's Jira system, introducing automation for triaging requests and providing consistent, risk-based reviews. This implementation resulted in improved visibility and stronger relationships between product and privacy teams. The team gained the ability to produce meaningful metrics on risk levels and SLA adherence, demonstrating its value to leadership and enabling it to scale effectively without increasing headcount.

Lyft

Brittany Rhyne

Privacy Analyst