DataRobot Case Studies World’s Largest Car-Sharing Marketplace Maximizes Guest, Host Experience with AI

Edit This Case Study Record

	World’s Largest Car-Sharing Marketplace Maximizes Guest, Host Experience with AI DataRobot

World’s Largest Car-Sharing Marketplace Maximizes Guest, Host Experience with AI

DataRobot

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Transportation
Applicable Functions	Logistics & Transportation Sales & Marketing
Use Cases	Fleet Management Fraud Detection Predictive Maintenance
Services	Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Transportation

Applicable Functions

Logistics & Transportation

Sales & Marketing

Use Cases

Fleet Management

Fraud Detection

Predictive Maintenance

Services

Data Science Services

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.

About 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.

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.

Impact #1	With AI, Turo has decreased its behavioral risk costs due to accidents and its fraud costs due to theft.
Impact #2	The greatest value is empowering Turo's team to focus on how best to serve the business versus getting mired in the mechanics of modeling.
Impact #3	Turo gets 80% of the performance for just 10% of the effort of before.

Impact #1

With AI, Turo has decreased its behavioral risk costs due to accidents and its fraud costs due to theft.

Impact #2

The greatest value is empowering Turo's team to focus on how best to serve the business versus getting mired in the mechanics of modeling.

Impact #3

Turo gets 80% of the performance for just 10% of the effort of before.

Benefit #1	Decreased behavioral risk costs due to accidents.
Benefit #2	Decreased fraud costs due to theft.
Benefit #3	80% of the performance for just 10% of the effort of before.

Benefit #1

Decreased behavioral risk costs due to accidents.

Benefit #2

Decreased fraud costs due to theft.

Benefit #3

80% of the performance for just 10% of the effort of before.

Download PDF Version

Overview

World’s Largest Car-Sharing Marketplace Maximizes Guest, Host Experience with AI

Operational Impact

Quantitative Benefit