Uber and Lyft may say otherwise, but ridehailing is inching closer to personalized pricing: the ability to charge the maximum price -- known in economics as the reservation price -- but enable that to be different for every customer, for an identical good or service. Considered one of the most elusive targets of consumer economics, personalized pricing is difficult to achieve. Even airlines, which have become savvy at price discrimination (using cookies and customer history) can’t compete with ridehailers. Here’s why: Uber and Lyft have far more data points (people take many more rides than flights) and do not have price aggregators (Google Flights, Expedia, etc.) that allow price comparisons.

As ride-hailing giants collect more and more data and perfect their algorithms, they will simultaneously enhance their ability to extract as much value from each user as possible.

Until now, Uber and Lyft have focused on riders’ locations and demand (e.g. time) to vary the price it charges and to trigger surge pricing when demand is high. But these companies  have the ability to go far beyond that, testing and eventually mastering the ability to price rides based on numerous other factors that could be considered indicators of a given individual’s willingness to pay. Some of these may include:

  • Phone type: iPhone users tend to be wealthier than Android users, meaning companies  could charge them a higher price
  • Battery power: Ridehailing companies  have already found that users are more likely to pay higher prices if their battery charge is low, for fear of getting stranded
  • Credit card: Companies could charge customers with more selective/prestigious credit cards higher prices
  • Phone number: Companies could issue higher prices to people who have phone numbers associated with higher income area codes
  • Ride history: Uber and Lyft could adjust prices based on a rider’s tendency to accept surge pricing and the share of pool vs. non-pool and select services

What could this look like? Imagine a young professional with a San Francisco area code who hails a vehicle from her iPhone. It’s late at night and her phone charge is down to under 10%. Since she usually takes Uber or Lyft for her job, she has a selective AmEx on file for payment. She also has a tendency to accept surge pricing, since she often travels at rush hour and can expense travel to her client. The company  has found a customer that shows signs of being more inclined to pay more and can shift its price accordingly.

But how is a company able to do this? There are two reasons:

1) Ridehailers know the upper limit of your pricing comfort

Uber and Lyft have an incredibly rich dataset for each individual rider. With riders taking an average of 4 rides per month (back in 2014), these companies  have built up a detailed history of each rider that will only continue to grow. Particularly on trips with same starting and ending points, they can see how much a particular rider was willing to pay in the past. Having introduced upfront pricing, companies can even test rider’s willingness to pay in real time by seeing whether riders hail the ride or close the app and try again.

2) Ridehailers can charge different prices for the same service

Uber and Lyft provide a customized and personal service to each user. By having the price offered on an individual smartphone, the company can charge different prices to each rider without other riders knowing. Even if they would know, it would likely be irrelevant: few people have identical starting and ending locations. Ridehailing can not only know the reservation price of individuals but also charge them this exact price in private.

While companies have caused outrage in the past with surge/prime-time pricing, they hold even greater power going forward. Having moved to partially mask surge pricing and continuing to collect greater amounts of data on its customers, these transportation companies  have the potential to achieve one of economics/business’ holy grails: perfect price discrimination.

The results of perfect price discrimination are mixed across parties. Uber and Lyft stand to gain by increasing prices and thus revenues. Drivers also stand to gain from higher fares from riders. Riders, on the other hand, are those that will be most negatively affected. As Uber and Lyft continue to take share of the market, riders will have fewer choices and thus fewer alternatives to paying these higher fares. Regulation may ultimately be needed to provide pricing transparency to riders and ensure that people are being fairly charged for similar services.

Image used with permission from noeltock.com


Author: Christoph Bjorn Meyer
MBA Candidate, 2017, at Stanford Graduate School of Business

Christoph is in his second year of business school at Stanford. He grew up moving around the world and became fascinated with how people and products get from point A to B. 
Having worked at an automotive startup (VisionFleet) and Ford, he's passionate about the transition into a new transportation future. 

LinkedIn | christoph.meyer@stanford.edu