The Amazing Ways Uber Is Using Big Data

Uber is a smartphone app that connects users who need to get somewhere with drivers willing to give them a ride. Since the service being launched, it has been expanded to many major cities around the world. What the more interesting is that Uber business model is rooted strongly in Big Data principle of crowdsourcing. Anyone with a car who is willing to help someone get from A to B can offer to help get them there. 

In their big data, Uber has databases of drivers, geographical location, customers, and credit card. These databases help to arrange the matching process when a passenger asks for a ride, he/she can instantly match with the most suitable drivers based on GPS information. Using GPS and time, Uber fares are calculated automatically by using a sophistication algorithms.

Surge Pricing Model:

While I am riding Uber, I have noticed that their pricing is dynamic and the calculation process is similar to a taximeter. The rider is charged based on the time and distance of the ride. 

Uber fares are based on a dynamic pricing model. For instance, the same route costs different amounts at different times because of factors such as the supply and demand for Uber drivers at the time the ride is requested. When rides are in high demand in a certain area and there are not enough drivers in such area, Uber fares increase to get more drivers to that area and to reduce demand for rides in that area. 

Uber uses big data for price surging. This means that as the demand for rides in the city increase, the price for Uber services increases as well. For example, Uber use GPS technology to identify popular restaurants or nightclub and based on the supply and demand, the price of a ride may vary. 

There are many factors that may influence Uber fare pricing. First, traffic conditions. For example, in Toronto, if the Toronto Transit Commission(TTC) shut down the subway system due to the event, such as a fire investigation, that leads to subway service delay, the fare price of Uber will go up.The second reason is that the high rates of supply and demand on a specific time and at a specific location. For instance, on New Year’s Eve 2011, a journey of one mile rising in price from $27 to $135 over the course of the night.

Rating Systems

Rating is the main thing in Uber. Riders may evaluate driver and driver may rate riders on a scale of 1 to 5 stars. Uber driver's career depends on his/her driver rating. Therefore, Uber Drivers must maintain their rate to be above 4.6 starts, otherwise, the Uber driver profile may be at risk of deactivation. At the same time, an Uber driver rates a passenger. If the passenger got three stars or below, the rider will never be paired with that driver again. Uber does not allow drivers to know what rating passengers gave them to protects passenger confidentiality.

To sum up, at Uber, big data and data analysis span many functions like data science, machine learning, fraud detection, and marketing spending. Uber collects data about trips, billing, and the health of the infrastructure and services behind the smartphone app. Uber is all about big data and Data Analytics in order to Deliver Extreme Customer Service. In the next blog, I will talk about the recent Uber scandal on how this company uses Big Data to avoid authorities.