New York cab fleecing holds lesson on data versus intuition

WIRED: Uber allows you to get a taxi when no one else can but a recent slip-up could end up costing it

WIRED:Uber allows you to get a taxi when no one else can but a recent slip-up could end up costing it

ITS LATE on New Year’s Eve night in New York. Your chances of finding a cab, even in a city usually brimming with yellow cabs, are slim. That’s okay, though: you pull out your smartphone and summon a car from Uber, a start-up that uses GPS and intensive data-crunching to guarantee its users a reasonably timed ride in cities from Austin, Texas, to Paris, France.

You get your ride: but then you get the bill. Travellers like Aubrey Sabala found themselves paying $107 for a 1.5 mile ride. In New York, some were paying more than six times Uber’s usual rate – even for New York, that’s a mite steep.

The users of the online taxi service are accustomed to paying a little bit extra for their ride. In San Francisco, the company’s home, its fares are generally twice as much as a normal cab fare. It turns out, however, that people are surprisingly willing to pay the premium. Uber uses a smartphone app which lets you time how long your (named) driver will take to arrive to the second. The drivers themselves are limo riders during breaks between expensive professional chauffeuring jobs, so the cars themselves are sleek, smart and air-conditioned.


But most of all, Uber applies internet start-up techniques to improve the responsiveness of its flotilla. Car operators and riders alike use the same smartphone software, which gathers and reports the location of hails, destination and trip duration back to the company. Uber can direct its drivers to the best locations in anticipation of calling patterns, and has a vast database of trip times to calculate the journey’s length. Uber’s engineers will even post some of their odder discoveries online (a recent chart revealed the gang affiliations of affluent San Francisco neighbourhoods – or at least in terms of their iPhone and Android use.)

But sometimes following cars that closely takes you to some strange places. As with traditional cab and car companies, Uber knew that New Year’s Eve would be a high demand night. But while normal cabs are required to keep their rates flat, causing shortages, Uber decided to let their fares fluctuate up, thereby keeping a relatively high supply of cars for those willing to pay the extra price.

It’s a strategy that Uber can pursue because it carefully avoids regulations as a cab service. The company hasn’t got a fleet of cars, and doesn’t do on-street hailing. Originally called “Ubercab”, it had to drop the suffix after complaints from San Francisco taxi operators. The end result was that while everyone who could afford the fluctuating rates got their ride, for travellers like Sabala, even the shortest trip became somewhat of a shocker.

The company emailed its users in advance of New Year’s Eve, and placed signs in its application’s user interface to flag the high fees. But if Uber wasn’t intending to fleece its customers, its previous attempts to make its service as user-friendly as possible may have worked against it. Uber customers press a button on their smartphone and a cab turns up; the billing and total is presented at the end of their trip and paid over the smartphone’s interface.

Even though the fare meter is shown on the driver’s smartphone (which is meant to be placed within the eyeline of the passenger), it’s entirely possible to go through an entire Uber ride without paying much attention to the mounting cost.

Is this what regulation is meant to prevent: the price-gouging of ordinary consumers in times of famine? With Uber, that accusation of malicious moneygrubbing does not quite ring true. The company stands to lose far more from the bad publicity of a few price hotspots than it does to grab some extra dollars. It’s still riding on venture capital funds, and seeking user growth and brand recognition in all its cities, rather than necessarily gaining its profits from its current rides. The company has also been scrupulous in all the corners that regulators might be suspicious: the drivers are vetted and ranked, the cars well-maintained and inspected. Indeed, it may even be the case that the high prices Uber charges are in part to avoid the suspicion that they are directly competing on price with licensed cab drivers.

Given such paranoia, the last thing Uber needs is to be seen as bilking customers through unclear charges: an accusation riders, existing cabbies and regulators could unite to seize upon. Instead, what we may have seen is a clash between the world of the pricing algorithm and the world of customer expectations. In a perfect market, pricing to moderate demand makes sense. If you really badly need the good that’s being selectively charged, then you can pay for it. Otherwise, you’ll just end up losing out or effectively entering a lottery. Uber would argue that cab riders fighting on street corners on New Year’s Eve have never had a choice before.

But customers also value consistency. And not every cab-hailer after a late night celebration is necessarily working as a perfectly rational, informed market actor. The lesson Uber learned in the first night of 2012 is something other companies who otherwise trust data over intuition might learn from.