This company connects mobility operators, data buyers, and riders by leveraging commute time for research tasks. It provides a platform for capturing real-time, location-triggered feedback from people in motion for market research and AI validation. Stride enables users to contribute data in exchange for mobility credits, improving transit experiences and unlocking actionable insights.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional market research methods struggle to capture timely, in-context feedback from individuals during their daily commutes and travel. This limitation hinders the ability of mobility operators and brands to gather actionable insights on user experiences and service performance in real-world environments.
Solution
Stride provides a location-aware mobile platform that incentivizes users to share real-time feedback on their travel experiences in exchange for journey credits. This creates a dynamic data stream for mobility operators and researchers to understand user sentiment and operational effectiveness. The platform leverages geo-triggered surveys and in-app feedback mechanisms to collect data at the point of experience. By integrating with existing research platforms, Stride facilitates rapid data acquisition and analysis, enabling continuous service improvement and user acquisition strategies for mobility providers.
Target Audience
Stride's primary customers are mobility operators, brands conducting consumer research, and AI development teams seeking real-world validation data.
Features
- Geo-fenced survey deployment triggered by user location and movement patterns.
- In-app feedback collection for rating trips, transit services, and specific travel touchpoints.
- User incentive system utilizing journey credits redeemable for mobility services.
- API integrations for seamless data ingestion into third-party research and analytics platforms.
- Mobile-first panel for rapid recruitment and deployment of research tasks.
- Support for importing survey instruments and custom data collection protocols.
- AI model validation through human-in-the-loop feedback on real-world AI applications.