What is Ride-Sharing Data?
Ride-sharing data is information collected and analyzed from rides taken through a ride-sharing service, such as Uber or Lyft. It includes details like pick-up and drop-off locations, trip duration, distance traveled, fare charged, driver ratings, and user feedback. This data is used to improve service efficiency, optimize driver allocation, enhance safety measures, and gain insights into customer preferences and behavior.
Examples of Ride-Sharing Data include information about trip duration, distance traveled, pick-up and drop-off locations, driver ratings, and passenger feedback. Ride-Sharing Data is used for analyzing patterns and trends in transportation, optimizing routes, improving service quality, and making data-driven decisions for ride-sharing companies. In this page, you’ll find the best data sources for Ride-Sharing Data.
Best Ride-Sharing Datasets & APIs
Email Receipt Ride-Sharing Data | Granular Transactional Data for Food Delivery/ Ride-Sharing Sector | Emerging Markets (APAC, LATAM, Europe & USA)
PredictHQ's Intelligent | Event Data | Traffic Data | Ride-Sharing, Transportation & Footfall Data | Global | Predict demand
Granular E-Receipt Data for Middle East | UAE / Kuwait / Qatar / Saudi | Ride-Sharing Data | Restaurant & Food Delivery Transaction Data
PredictHQ's Intelligent Event Data | Ride-Sharing, Transportation & Footfall | Mexico City | April 2023 - March 2024
Granular Ride Hailing Data for Emerging Markets | Consumer Purchase Data | Global Alternative Data | Uber, Lyft, Grab, Didi, 99, Gojek
Monetize data on Datarade Marketplace
Ride-Sharing Data Use Cases
- Overview
- Datasets
- Use Cases