Uber Pool: The Future of Transportation?
We all love (and hate) Uber for what their product currently is: a (relatively) cheap and convenient way to get from point A to point B. I remember my first experience using Uber, which stemmed from my hatred of calling a taxi cab company to go out to the bars. Usually, I’d have to call a random cab company I found online, request a cab at a street corner that I’d have to describe, and then ride in a dinky cab with out any knowledge of pricing. Then, along came Uber. At the time, Uber wasn’t really trying to reinvent the taxi cab system: just take a user from point A to point B. But all the pain points of requesting at a certain location, taking the most efficient route, and best of all, a well kept and modern car they hit right on the money. I (and the rest of the consumers) never looked back.
So now it’s interesting to take a look at where Uber is now. I would argue that Uber has grown and expanded the personal transport market. Where I once maybe took 5 to 10 cab rides a year (mainly for bars or the airport), I now take easily that many Ubers in a month, from seeing friends to going out to eat to grocery shopping. It’s pretty clear that Uber is not only trying to takeover the taxi industry but also transportation as a whole, by catering to everyone.
I’m writing this from my perspective in America, as that’s where I’ve had the most interactions with personal transit and public transit. In most American cities except for maybe New York City, we have pretty horrendous public transit. It’s just a given that America was built on cars. Everything was about owning a Ford or a GM car, from the status symbol to the convenience to the family road trips. So instead of like European cities, our public transit money went into building road infrastructure and subsidizing gasoline. We were investing in our future of personal, convenient transport.
Fast forward 50 years and we are increasingly becoming more urbanized with a smaller reliance on long car rides and a bigger emphasis on quick trips. Uber covered the personal trip part with UberX and UberBlack but what about the average consumer who just wants to get from point A to point B and is willing to sacrifice convenience for a much lower cost? There’s where UberPool and all the offshoot products come from (and unrelated products, such as the Uber credit card or the Jump bike acquisition).
First, let’s look at UberPool. It gets you from point A to point B but we’re now going to take slight detours to pick up and drop off passengers going in the same direction as you. So as a passenger, you won’t get to picked up or dropped off as quickly but you’ll be sure to get wherever you need to go within a reasonable time. The user pain point of the original UberX product was, unfortunately, it was just too expensive. So how can Uber bring down the average price it charges per consumer AND make more money per ride? By using smart routing algorithms to place consumers in the same car going in the same general direction! This allows each user to pay a small discount but since there are now more users per ride, the total amount Uber (and the driver) makes goes up. The only bad part is since Uber shows upfront pricing (more on this later), if only one user requests an UberPool, then Uber (but not the driver) will lose since they charged the user a discounted ride and only had one total customer. This is where the next couple of products come into play to help solve Uber’s pricing pain point: to help Uber optimize their upfront pricing.
At this point, Uber knows the major pain point that consumers have is the price point. Ride sharing is currently a commodity; there’s really nothing differentiating Uber or Lyft or Grab or Didi or any other rideshare company besides pricing. All are safe, reliable and easy to track via smartphone. So how does Uber calculate and infer the best upfront price to show to account for potential for only rider? Data. And lots of it. Because at the end of the day, the upfront pricing is a probability game. If Uber knows there is a low chance that there will be a second rider on a given route, they will show a high upfront pricing. On the flip side, if Uber knows there is a high chance that there will be a second rider on a route, they could show a low upfront pricing to attract users. There are millions of more potential scenarios and with more data, Uber can calculate the best pricing to show.
The first version of UberPool was step one, to validate the idea of consumers embracing carpooling for the allure of a cheaper price. Consumers loved it.
The next step was to collect data. Introduce: The Uber Credit Card. Now you’re asking, why would a rideshare company care about people’s spending habits? Because using people’s spending habits, Uber can infer where and when, Uber can best predict where people are requesting Uber’s from and to. Maybe even close to real time. Uber sees a bunch of people are using their credit card at a specific bar? That probably means at closing time, there will be people heading home and hopefully, in the same direction home.
The next step is to have users wait longer after requesting a ride to increase the chances of a second user going in the same direction. If I had to guess, there aren’t very many people requesting UberPool rides at the same time. But given enough time, the chances go up dramatically. So now Uber is having users wait up to 2 minutes before dispatching a driver to pick up a user. I think this is currently in an early testing period to validate if users are even willing to wait. But if I had to guess, I think the average user is willing to wait for a very reduced price.
The end goal, unrelated to collecting data, for getting pricing down is either self driving cars or getting users to do drive themselves. What do I mean by this? Look at the Jump bike acquisition. There’s a new form of short distance mobility emerging and instead of paying someone to drive you 3 miles, you just hop on a scooter or a bike and ride yourself for those 3 miles for pennies on the dollar.
What’s the next step for Uber? I’m not sure but what I guess is Uber ultimately wants to try to guess where from, where to, and when users want a ride before the user even requests it. This gives them ultimate leverage around upfront pricing and how to dynamically change it based on certain user behaviors and routes. This can also help them estimate supply based on demand. The ultimate goal for Uber is how can they leverage technology to optimize pricing for both the consumer, driver, and Uber’s bank account.
Does the future of transportation look increasingly less about transportation technology and more about data and optimizing routes and pricing?
