Even as its business continues to grow at a rapid clip, on-demand car service Uber has a bit of a reputation problem. Fairly or not, some call it a luxury for those who can afford it, while even loyal users are (rightfully, it seems) upset about its surge-pricing practices. Now, Uber is using data to show that — at least in one large city — the company can’t be accused of catering only to rich riders.
According to a blog post from on-demand car startup Uber, in Chicago, “median income in a neighborhood has no meaningful relationship to Uber’s level of service in that neighborhood.” The company analyzed its ridership data in the city and found that for every $1,000 increase in median income, the expected wait time for an Uber car drops by 3 seconds and the probability of fulfillment increase by 0.3 percent.
The statement is technically accurate, although maybe a little misleading. Without the values on its X and Y axes on its charts, it’s difficult to gauge exactly what those differences might mean. According to the the census data that Uber used — as well as data from Rich Blocks, Poor Blocks — the expected wait-time difference between Chicago’s poorest and richest neighborhoods could be about 4 minutes (which isn’t that big in the grand scheme) while the expected probability of a ride being fulfilled in the richest neighborhoods could be about 25 percent higher (which seems a little bigger).
Whether or not this data helps dispel — or reinforces — the myth of Uber as a status symbol for the yuppie class might depend on your point of view. The devil’s advocate might argue that there are more riders and, thus, more drivers in richer neighborhoods. Perhaps richer riders tend to call black cars instead of the less-refined UberX fleet, which leads to higher profits for Uber and its drivers. It’s still a business, after all — and it still might be a better option in low-income neighborhoods than waiting for a taxi that might never come (or stop) or adhering to a public transportation schedule that often might be less than reliable.
However, the fact that Uber has the data and knows how to analyze it certainly represents big difference between today’s data-driven businesses and those of old — which is something we’ll discuss in detail at Structure Data later this month in New York with senior data scientists from Uber, LinkedIn and Airbnb. When you measure everything about the customer experience, it should be a lot easier to improve it, and it’s also a lot harder to hide behind claims of ignorance.
If Uber is serious about disrupting transportation across economic strata, it has the data to show how good a job it’s doing and also to help improve on that mission. Uber, for example, knows where riders are being picked up, where they’re being dropped off and where its cars are circling. It knows who’s requesting cars on what kinds of devices and how long they’re waiting.
It, like all smart companies, will optimize its business for whatever goals it deems important, and we can applaud them or demonize them accordingly. And we can rest easy doing so, knowing that they know exactly what they’re doing — or at least as much as the data can tell them, which it turns out is quite a bit.