World’s Largest Car-Sharing Marketplace Maximizes Guest, Host Experience with AI
Customer Company Size
Large Corporate
Region
- America
- Europe
Country
- United States
- Canada
- United Kingdom
Product
- DataRobot AI Cloud
- MLOps
- AutoML
Tech Stack
- Machine Learning
- Artificial Intelligence
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Transportation
Applicable Functions
- Logistics & Transportation
- Sales & Marketing
Use Cases
- Predictive Maintenance
- Fleet Management
- Fraud Detection
Services
- Data Science Services
About The Customer
Turo is the world’s largest peer-to-peer car sharing marketplace based in San Francisco. The company connects guests and vehicle owners for mutual benefit. Its popularity has grown with over 1.3 million active guests and over 85,000 active hosts powering more than 160,000 active vehicles across 1,300 unique makes and models. Turo operates in 7,500 cities across the US, Canada, and the UK, allowing guests to skip the rental car lines and book the vehicle of their choice from local hosts. At the same time, the car’s owner earns extra cash on a vehicle that would otherwise be sitting idle.
The Challenge
Turo, the world’s largest car-sharing marketplace, sought to optimize its operations by leveraging data insights. The company connects guests and vehicle owners for mutual benefit across the US, Canada, and the UK. With over 1.3 million active guests and over 85,000 active hosts powering more than 160,000 active vehicles across 1,300 unique makes and models, Turo needed a way to efficiently manage its vast operations. The company aimed to optimize pricing, risk, and marketing strategies using data insights. However, the sheer scale of its operations presented a significant challenge in terms of data management and analysis.
The Solution
Turo turned to DataRobot's AI Cloud Platform for machine learning and augmented intelligence solutions. The platform influences three main parts of Turo’s business: pricing, risk, and marketing. Hosts may choose to set their own pricing or use Turo’s automated pricing recommendations based on supply/demand forecasts and vehicle characteristics. To minimize risk, the company relies on ML-based underwriting models to determine the likelihood of accidents, expected severity, and expected collection. For that, it weighs a number of factors, including type of car, city or non-city use, time of day booked, age of the driver, and even how far in advance the guest reserved a vehicle – helping set pricing. Additionally, they develop live fraud detection models. Turo also uses machine learning to help predict the lifetime value of customers, enabling them to set marketing budgets and determine their marketing return on investment.
Operational Impact
Quantitative Benefit
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