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New Snapper integration brings Rate-My-Ride to operational dashboards

First-of-its-kind partnership shows rider feedback and real-time network performance side-by-side in a unified interface

November 29, 2023

Qualitative rider data from Transit can now be seen in Snapper’s Mosaiq Insights dashboard, which provides transit agencies with network performance analytics.

The rider feedback comes through GO, Transit‘s step-by-step navigator. GO tells riders when to leave for their stop, when to transfer, and more. It also prompts riders with Rate-My-Ride questions at just the right moment, like “Is there trash or refuse at this stop?” while they’re waiting, and “Do you feel safe onboard this vehicle?” as they ride.

Rate-My-Ride makes it easier to gather specific, in-context information about the rider experience, so agencies know how to improve it.

Each Rate-My-Ride answer is tied to a trip ID, stop, vehicle, route, and time of day, but no personal identifying information about the rider is stored. The answers are shared with agencies in a dashboard provided by Transit, where staff can see the results overlaid on a map and filter to see how riders’ feedback changes by route or time of day.

Rate-My-Ride data is designed for seamless integration into other tools agencies use, and its included response attributes (like trip ID, stop, vehicle, route, and time of day) make it easy to match with network data.

Enter Snapper.

Snapper’s Mosaiq Insights platform connects schedule and real-time data to compare how a transit system is functioning on the ground against the agency’s goals. The platform surfaces high-level punctuality and reliability metrics to make sure buses are on time and on course, then makes it simple for network planners and schedulers to dive in and make improvements to the network.

Through Transit and Snapper’s partnership, agencies get a 360-degree view of the rider experience by pairing Snapper’s analysis about how the transit system is performing against expectations, with Transit‘s Rate-My-Ride feedback from riders about their experience using the system.

For example: if a bus is consistently late, but its headways are frequent and consistent, agency staff can see whether riders notice the issue. If a bus is consistently late, and riders are reporting it, the agency can investigate what’s causing the tardiness, or update schedule data to more closely reflect the reality on the ground. Or: they can see if a previously uncrowded bus is now regularly reported as crowded, and if they may need to improve headways on that line.

Agencies can receive actionable insights instead of being overwhelmed by a mountain of raw data, and they can prioritize the changes within their transit system that will improve the rider experience most.

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