How Uber Depends on Data Analytics to Deliver Extreme Customer Service – Face To Face With Uber’s Chief Data Architect

From a simple limo hailing app for friends to the world’s go-to taxi app. Uber’s growth in the approximately 7 years of existence can be described by one word, “Phenomenal”.

But there’s another way to define Uber, one that not many have given thought to.  Uber is a Big Data company, on the likes of Google and Amazon. It not only uses existing data in its banks effectively for its business operations, but the process of gathering data – data from drivers, data about drivers, data of passengers, data about passengers, data of traffic systems around the world, transactional data – and analyzing all of it in real time, continues.

I caught up with Uber’s Chief Data Architect M C Srivas on my recent trip to San Francisco. In the course of the hour-long conversation, among many things, Srivas spoke of what data analytics means for Uber, and how innovation in data is being used to further what is now popularly known around the world as “the Uber model.”

Raj: I have been tracking for a while now how data can be used to drive “extreme customer service”. Uber has done some exciting stuff, matching supply and demand and estimating pricing. Where do you see Uber going in the next 3 years where data and the enablers are concerned?

Srivas: Well, it’s already the main ingredient. Let me give you the high level picture here. The way Uber makes money is when its drivers are happy and also the passengers are happy. That’s what makes Uber happy. The driver is happy when his taxi is always hooked. Essentially, he wants a passenger in his backseat all the time in order to keep making money.

For the passenger, he is excited when the price is the lowest; the least amount of money he spends to get from point A to point B. That, too, in the shortest amount of time. That’s what makes him happy.

That’s the real part of data analytics, it’s amazing.

“If you look at the last two years, its impact on the bottom line, you will realize that the average trip ride price paid by the passenger has actually has gone down by 50%. The average amount of money a driver make has actually gone up 30%.” Yet, in spite of the fare going down, the drivers are actually making more money. That’s the amazing thing about matching these two factors – both sides should be happy. And this is where Uber has an edge over others; that’s our secret. This is where all the other guys who tried this got beaten back and lost. There are many companies which think of it as just a car hailing app where one needs to make these two ‘people’ get on the way and make some money. No, you don’t make money, you got to make the other people money first. And doing that efficiently is very difficult.

“So analytics is like the core of the business. And there’s a barrier to entry for anybody else who wants to get into this business. It’s very difficult.”

Raj: Uber has got a few years’ lead. It’s capturing lots of data with every ride of its cabs. But why do you think others have not been able to catch up?

Srivas: It’s two things. The first is data and how well we do this. How well does Uber understand traffic pattern across every city in the world – in fact in 70 countries? More importantly, our ground operations are phenomenal, the quality of the cars, the quality of the drivers is ‘Uber’, that’s why the service is called Uber. It’s very high quality. So doing this low cost-high quality thing is the ground up mission of our every city unit ground operation.

Factors that are considered are – how do you inspect that cost, how do you go and get 500 drivers before even operations start….you need 2000 or so passengers before the launch. The drivers will not operate unless there are passengers. The passengers won’t come unless there are drivers. Then, there are city-specific regulatory hurdles that have to be overcome, too.