Uber is a great example of a company using big data for price discrimination.
You may be familiar with Uber.
It's a very fast-growing company that provides
a taxi service app that operates in more than 50 countries today.
As of 2015, Uber was valued at more than $40 billion by venture capital firms.
Part of the reason for Uber's success is that it's able to effectively price
discriminate between customers using what's called surge pricing or dynamic pricing.
And what Uber does here is when the market demand outstrips available supply,
in other words, at peak times Uber raises the fare on their app.
This encourages more drivers to take to the road which expand
supply and it also helps to weight down on demand a little bit,
and then finally it maximizes profits for Uber.
The idea is that the company can take advantage of
the low-price elasticity of demand at busy times.
If it's five o'clock in the afternoon and lots of people are trying to go home,
well, those people aren't interested in waiting
until 6:00 or 7:00 or eight o'clock at night to get home.
They're willing to pay a higher price.
Now some economists have criticized this policy,
especially during emergencies like freak weather events and
terrorist attacks as being bad for consumers and maybe being unfair.
And there's some validity to those concerns and Uber has responded to
those concerns by eliminating surge pricing during those kind of times.
So, it's not about the company taking advantage of consumers,
it's instead about the company trying to maximize profits in a fair and reasonable way,
based on customer demand.