The Subtle Art of Differential Pricing
Data really is the new oil. For some corporations (like tech giants Facebook and Google), it forms the very basis of their existence. For others, it forms the backbone of their pricing strategies. Case in point — ride hailing majors like Uber and Ola. We come across a lot of instances of people complaining that they were charged differently for a ride as compared to another user for essentially the same route at the same time (like this gentleman here). Let us try to delve a little deeper into the factors that Uber/Ola possibly consider before they decide what price is right for a particular customer.
Before we start, please note that all the conclusions that I have drawn here are based strictly on anecdotal evidence. The pricing algorithms that these companies use are (obviously) proprietary in nature and we’d never know for sure whether they are indeed using these techniques or not.
The Uber app on your phone is capable of detecting battery information in order for it to determine whether and when to go into power saving mode. A collateral usage of this information is for determining how sensitive you are to a surged price at any given moment. Behavioral economics (and common logic) suggests that a user who is low on battery is far more likely to accept an increased price because of the fear of being stranded with a dead phone as compared to a user with a full battery who can afford to wait a few more minutes for the prices to go down again. In fact, Uber’s former Head of Economic Research, Keith Chen had pointed out this behavioral pattern himself. He, however, asserted that Uber would never use battery life information to try and push the customer a higher surge price. It is nonetheless a very interesting psychological fact of human behavior and is used by Uber (and perhaps now even Ola) to understand the price sensitivity of demand for their service.
Now, from your phone’s battery to your phone itself! Ola’s Terms of Service state that they collect information regarding “The manufacturer and model of your mobile device”. Tech website Gadgets To Use conducted a very interesting experiment on Ola’s pricing algorithm. They tried to book an Ola Micro ride on the same route at the same time but from two different devices. One was a relatively low end smartphone — the Moto G4 (without any balance in the Ola Money account) and the other was the high end iPhone 7 (with balance in the Ola Money account). While Ola gave them an estimated fare of ₹126 on the Motorola device (without any surge pricing), it gave them an estimated surge price of 2X on the iPhone for the exact same route! This seems to suggest that your fancy smartphone is actually a curse in disguise. While one line of thought argues that it is okay for corporations to charge more to those who can clearly afford to pay more, deciding the capacity of a person to pay based on the smartphone they’re using is a very lousy idea.
Another factor that could possibly influence the price being demanded from you is the track record of your behavior, i.e. the ratings that your drivers give you. If you are the kind of person who often keeps the driver waiting, or if you frequently use the service after getting drunk and mess the space up, these companies might want you to pay more for the trouble you cause. In an article in The Guardian, Arwa Mahdawi quotes one of her colleagues as saying that when he switches from his personal credit card to his corporate credit card in the Uber app, his quoted price often decreases, and that this might have something to do with his kid frequently vomiting in some cabs. “There may well be an algorithm that has figured out that dad-Dan is not as desirable a passenger as corporate-Dan, and charges him accordingly”, Arwa hypothesizes. Key takeaway? Behave!
And finally, your pick and drop points. This one is a no-brainer really, and something that Uber has actually acknowledged it does. The company called it “route-based pricing”. The app basically tries to identify the routes (and time of the day) when you are most likely to agree to pay more. If, for instance, you book a cab from one posh neighborhood of Mumbai to another during peak hours, Uber/Ola might charge you a premium, because the AI predicts that you obviously have the capacity to pay more since you are choosing to use a cab between two tony areas during rush hour.
Nobody really knows how much of this actually happens. And these corporations won’t ever let us find out, because then they would run the risk of offending their customers. Another thing that they’d never like to share is exactly how much data about us they are collecting and where they are using it. You can choose to either dismiss AI and Machine Learning as just another tech innovation, or you can start getting ready for your future robot overlords, but you can’t deny that corporations are using data about your behavior to play you — and there’s nothing that you can do about it.
