How does technology allow the rise of car sharing?

But how do you ensure that consumers can find available car-sharing vehicles wherever they want? How do you know when a vehicle needs to be cleaned? Or, how do you define geographic areas of interest for car sharing?

A data-driven business model

The real “cogs” of technology flexible car-sharing. This enables providers to fine-tune their strategies and resources according to the actual needs of the users, which is an essential element of providing a sustainable and efficient car-sharing service.

And it starts with defining an area of ​​operation in which vehicles can be rented and dropped off. To define areas with high rental potential, providers rely on technology, data, and artificial intelligence. From the socio-demographic profile of the area, to the percentage of motorists, the number of points of interest (restaurants, museums, etc.) and going through the established business, the criteria are multiple.

Once the areas are selected, demand forecasting is also essential to ensure that cars are in the vicinity where they will be quickly re-rented. When that doesn’t happen, the algorithms automatically adjust the rental rate to make the car park more attractive and thus encourage car rental. The goal here is to prevent a technician from traveling to transport vehicles.

In the long run, the technology is constantly analyzing customer usage and area attractions to better identify needs and adapt the service to actual needs.

Technology in the service of customer experience

Another determining factor contributing to the success of car sharing is the customer experience. And the next one starts with the maintenance and operation of a vehicle. If free-floating car-sharing manages to impress many enthusiasts around the world, it is thanks in large part to its speed and simplicity. The software developed by the suppliers makes it possible to select a car and rental period from the smartphone, fill in all the administrative documents and unlock the car with just a few clicks. This instant service is a major advantage over other forms of shared automobile mobility.

Once the car is in hand, the continuity of the customer experience is strongly linked to its operating condition and its cleanliness. Car-sharing fleets must be in good condition and clean, despite the high rents. Again, this is the technology, and more specifically the machine learning algorithm, which allows suppliers to take full visibility and predictive maintenance measures of vehicle conditions. Predictive maintenance involves an algorithm that receives and integrates data related to usage, latest cleaning times, vehicle models, and – most importantly – customer feedback on a vehicle learning app in a machine learning process.

What new progress is expected?

Technology, and especially artificial intelligence, has emerged as the key to success in the car-sharing sector, in addition to an attractive fleet. Although they are almost invisible to the eyes of consumers, they are cogs that enable services tailored to the needs of different cities and consumers.

By making the evolution of mobility more “predictable”, technology providers continue to adapt to the challenges of the environmental crisis and to reduce the rate of motorization in our cities.

There is still a lot of potential for improvement in supply management. It is important to find solutions to better identify what consumers need, when and where. This makes it possible to adapt the offer consistently with these parameters and thus with the need for individual dynamics.

The relocation argument is already very successful, but the challenge here is to improve the availability of vehicles in high demand areas to ensure rent. In this case, artificial intelligence and its reliable calculations will play a bigger role in the future and take sustainable mobility to the next level.

Collective possibilities, thanks to car sharing, lots of data on mobility requirements constitute important information for creating sustainable mobility of tomorrow.

First, because it makes it possible for users to improve their daily lives, for example, thanks to motorists for tackling the growing challenge of electrical mobility by providing information directly on the charging infrastructure available on their rides from their car-sharing applications. Digital cartography.

But also because this data allows car-sharing operators to predict when, how and who needs a car – an essential prerequisite for the future development of autonomous and efficient car-sharing.

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