Ever wondered how the price of the ride is predicted just by providing the destination location? It’s all because of AI through which the price prediction of a ride has been possible. It is only through artificial intelligence that the existing services like Mopedo determine the price of your ride.
It is the same hymn before the usual cab booking slot that sends you promotional messages just in time! Predictive analysis, machine learning, and deep learning are the different facets of AI which are bound in every possible way to make the service better. Mopedo has been significant since its endorsing features of AI have been deployed with a similar algorithm for better ride scheduling.
Though It has been difficult to handle scattered and non-numeric sentiment data, AI has proved as a better approach through which analyzing Sentiments through structured numeric data has been enough to gain intelligence.
Every tiny aspect of insights that are to be deeply discussed and even cannot be disclosed on the brand can be decided by AI. The user-generated information through the app can also be scanned by AI. The product and service enhancements made possible by this intelligence can be extremely useful in shipping the rider’s next move for marketing.
In the prompt of the driver’s experience, one may be well-versed with the routes, and others may not have the same. For this purpose, the drivers can be served with the AI engine that provides optimized routes that can even assign particular routes to get a better experience. This helps the drivers in getting passengers to be in their zone and comfort.
Every segment of data from the choice of vehicle and time of booking to the pattern of the rider’s travel has been carefully personalized. This personalized information can be segregated from the magnitudes of the mediocre to provide proper communication and services.
As many of us are exercised with graphs extrapolated during school. Unsurprisingly, AI can even extrapolate the raw data that enable business owners to make informed decisions to strategize the demand of application services. Analysing the areas and time of demand from these graphs can make more taxis available, to benefit the riders who will be looking for a bike taxi service as soon as they step out.
These optimized routes can be analyzed with respect to traffic and time from the experienced drivers’ riding data. This data also helps in determining the places with high concentration and areas bounded up during peak hours.
This shows how quite evident AI is being inevitable in Bike taxi services. In the future, AI can become a bounded integral part of ride-hailing services. It is rather a mandatory necessity to incorporate Mopedo indulged with all its AI functionalities being of utmost importance. This ride-sharing service can even come up with the autopilot service as long as AI rises in continuous development.