By now you would have heard of Uber, a smartphone-app based ride sharing service, which connects users who need to get somewhere with drivers willing to give them a ride.
Using their smart phones, each driver and passenger is represented as “things” in a connected network and are able to interact with each other in real time. These connections and interactions have enabled Uber to collect massive amounts of data and utilize it to build a business model based on the Big Data principle of crowd sourcing.
Utilizing the vast database of drivers in all of the cities it covers, Uber is able to instantly match passengers with the most suitable driver, when they ask for a ride.
Uber has applied for a patent on its method of Big Data-informed pricing, “surge pricing”. Uber’s algorithms monitor traffic conditions and journey times in real-time (collected by drivers on the road), combine it with GPS data and makes adjustments to the time that the journey is likely to take.This is vital for Uber’s pricing as it is based on time taken for the journey. With the algorithms, fare calculations can be adjusted as demand for rides changes, and traffic conditions mean journeys are likely to take longer. This is the difference between Uber’s pricing and traditional taxi companies’, which is based on distance covered.
This is an implementation of “dynamic pricing” – similar to that used by hotel chains and airlines to adjust price to meet demand – although rather than simply increasing prices at weekends or during public holidays, it uses predictive modelling to estimate demand in real time.
Insight into Uber’s data(New York), revealed that a vast majority of Uber trips have a look a like trip – a trip that starts near, ends near, and is happening around the same time as another trip. Uber utilized the data and created the Uberpool service. The service allows users to find others near to them making similar journeys at similar times to share a ride, and is all about getting more butts into fewer cars. This translates into less congestion over time and cost savings for riders.
Uber CEO Travis Kalanick has claimed that the Uberpool service will cut the number of private, owner-operated automobiles on the roads of the world’s most congested cities. In a 2014 interview, he said that he thinks the car-pooling Uberpool service will cut the traffic on London’s streets by a third.
Since its launch in 2014, Uberpool has been rolled out across 40 cities, such as Los Angeles, London and Chengdu. Singapore is the third city in South-east Asia, after Jakarta and Manila, to land Uberpool.
In Indonesia, a local grown startup, Go-Jek, uses the same principle but connects Ojeks (Motorcycle Taxis) instead of cars to passengers, has been flourishing.
As the competition plays out, we can expect the winners to be those who make the best use of the data available to them, to improve the service they offer to their customers.
The most successful is likely to be the one which manages to best use the data available to it to improve the service it provides to customers.
References were made from “The Amazing Ways Uber Is Using Big Data“
Jul 8, 2016