Our Maps SDK for iOS and Android helps JUMP riders locate their dock-less e-bikes. Our Maps power the behind-the-scenes “rebalancing” tool — a critical factor in allowing the company to scale efficiently.
Under the traditional bikeshare model, people park bikes in designated docks around the city. When ushering in dockless bikes, it’s a double-edged sword— consumers have the flexibility to park bikes where it’s most convenient, but without a dock, they need hyper-granular location information to find a bike.
Without docks, JUMP relies on our Maps SDK for iOS and Android to help users locate bikes in the field, and park them properly. JUMP’s development team built a map-based visualization that shows users the rules of the service in an intuitive, visual way. Bold red lines outline geofenced service areas where JUMP operates, black dots indicate charging stations, and black polygons identify no-parking zones.
When you’re running a bikeshare fleet, you’re paying close attention to trips-per-bike-per-day. The more trips one bike takes, the more money the bikes make, and the less time wasted per asset.
The key behind those numbers is the rebalancing tool—a logistics and operations dashboard built from scratch using GL JS and the open source spatial analysis tool: turf.js. JUMP’s Director of Operations Intelligence saw that as fleets grew, the traditional dispatcher-based system bikeshare companies use to communicate with their rebalancing team was not scalable. In an effort to visualize the fleet and empower the ground team to dispatch themselves, her team built the rebalancing tool on their own, going off of Mapbox guides and documentation and examples as their guide.
Just like the in-app map, the geofenced service area serves as the canvas for the rebalancing tool. Icons layered onto the map visualize real-time asset location, charge level, and repair status.
It’s critical to address out-of-bounds bikes quickly to uphold operational agreements and boundaries set with cities and regulators. Geofencing allows the rebalancing team to get a notification the moment someone parks a bike outside of a service area.
The team has even experimented with predictive modeling, creating a hexbin map to help them compare average demand (app opens) in a given area during rush hour to available assets (bikes) on the ground.
So why build such a visual tool for internal use only? Pierson says it not only removes the bottleneck of a single dispatcher—it empowers the rebalancing team to study the map, plan their routes, and build out their day. With this visualization in everyone’s hands, the collective team can spot inefficiencies faster than a single dispatcher ever could.
Visualizing critical issues like this helps get bikes up and running faster, and ultimately helps JUMP make more money.