A substantial portion of Uber’s employees are statisticians and engineers who work in its “math department,” using the data the company gathers from customers to develop ever more sophisticated algorithms that can predict demand. The mass of data that Uber collects has generated some surprising insights—Kalanick says, for instance, that by looking at demand on days when the San Francisco Giants play at home, his statisticians can predict wins with a slight edge over the Vegas odds. Whether or not you’d be willing to put money behind this claim, relentless data crunching has clearly allowed the company to continuously improve the speed with which passengers can find cars—or cars can find passengers—by providing increasingly fine-tuned forecasts of demand, neighborhood by neighborhood.
The data and the ability to set fares are what let the company patch the holes in the current system. A car is always available (because at peak times, such as New Year’s Eve, the company raises prices until supply matches demand). The car is well maintained. And as long as you’re willing to pay the fare, that car will take you wherever you want to go, without regard to race, ethnicity, or ZIP code.
Uber’s service is expanding to many cities, with a varying choice of vehicle types and rates as in below in NYC
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