Hello everyone and welcome to ZD Tech, ZDNet’s daily editorial podcast. I am Precilia Ahissou and today I explain to you why renting a self-service scooter must be very simple for the user, but is incredibly complex on the technical side.
Nowadays, traveling in the city is simple. You unlock a self-service scooter, car, or electric bike from your smartphone, and off you go. But of course, you do not suspect the incredible technical complexity behind these simple gestures.
First, rental companies need to define their area of operation. That is to say, which are the places in the city where the vehicles will be dropped off and rented to earn money. And for this, data analysis and artificial intelligence are strongly used.
On the data side, several criteria are analyzed, such as the socio-demographic profile of the area, attendance, or the number of restaurants, museums, businesses… in short, potential destinations for customers.
On the artificial intelligence side, the technology makes it possible to predict demand in order to ensure that available vehicles are in neighborhoods where they will be rented quickly.
And if not, the algorithms should adjust the rental rates to make the area where the vehicle is parked more attractive.
This is essential, because it makes it possible to optimize the service of course, but also to reduce operating costs. Yes, because it avoids having a technician travel in person to relocate the vehicle.
But where technology is even more crucial is on the customer experience side. Because yes, the customer experience is certainly the most important factor in the success of a shared mobility service.
From the reservation on smartphone to the handling of the vehicle, the service must be fluid, and above all instantaneous.
Duration of rental, registration of administrative documents, ergonomics of the application and the customer journey, the immediacy of the service is one of the major assets, assures in a column published on ZDNet Olivier Reppert, the CEO of Share Now, a company specialized in free-floating car-sharing.
Especially since for car rental, the customer experience is punctuated by multiple stages. Such as the assessment of the working condition and cleanliness of the vehicle.
Finally, the maintenance of vehicle fleets is also fueled by technology. These are machine learning algorithms that provide complete visibility of the condition of vehicles in order to adopt predictive maintenance measures.
These algorithms use vehicle data, the time of the last cleaning, the vehicle model, but also the comments left by users on the cleanliness of the vehicle.