A car sharing company uses the Zoba platform to build a network in a new market and to increase utilization in a current market.
A car share company that operates a fixed-pool model was expanding into a new city. In order to effectively plan and ensure that they were able to be competitive immediately upon entry, they wanted to predict demand before they launched.
Their data scientists used the Zoba Platform to model the relationship between demand at pools in cities that they were currently operating in and environmental data like population movement, weather, and points of interest.
Predicting Demand in a New Market
By looking at the same environmental data in the new market, the car share company was able to predict high demand areas at nearly a city block level of granularity.
Optimizing Operations Before Launch
This company then used the Zoba Network Design Optimizer to recommend the first locations for pools in their new market and the optimal amount of vehicles for each pool. This allowed them to more efficiently negotiate for parking locations, compete immediately upon market entry, and drastically speed up adoption of their service in the new market.
Additionally, this company used the optimizer to recommend a redistribution of vehicles in cities they were already operating, recapturing several percentage points of utilization that they were leaving on the table.