Welcome to the world of ‘black box’ pricing.
Imagine you got your supermarket’s weekly flyer in the mail. Oh, wow. Eggs are $2.89 a dozen. That’s a good deal! And then your neighbor comes out and picks up the same flyer from the same store from his mailbox. But on his, eggs are $2.49 a dozen.
Sounds insane. But it’s happening to people all over the world right now on their computers.
Welcome to the world of “black box” pricing. Because web sites can deliver data on the fly, companies are now able to modify their offers based on a swarm of invisible information about the customer.
When you load a website, your browser communicates with their server and sends them all kinds of stuff. What kind of computer and browser, your connection speed, your geographical location, what ads you’ve clicked on recently… the list is very long and getting longer.
Companies are now using that data not only to shape your Internet experience, but determine how much you’re willing to pay for goods and services. They’re running a host of calculations that add and subtract dollars from prices to find the one you’re most likely to pay.
It sounds abstract, but we can show you multiple real world examples that you can test for yourself.
The Princeton Review is a college admissions and test prep service. They’ve been in business since 1981 and offer a variety of services, but the most popular is their SAT program. Because this is 2016, you can take it online, so it doesn’t matter where you live.
But a recent investigation from ProPublica uncovered something deeply weird: it does matter when it’s time to pay the bill. Even though these online programs contain the exact same material, shoppers in different ZIP codes were given wildly different prices.
The lowest price — $6,600 — was the most common. But in 349 of the sampled ZIP codes, the cost went up to a whopping $8,400. And what was the common factor across those locations?
Asians. Nearly every one of those ZIP codes had a measurably larger percentage of the population that was of Asian descent. And we all know the stereotype of how important good grades and educational achievement is to that community. So, naturally, Princeton Review believes they’ll pay more.
This isn’t illegal, surprisingly. It’s no different from how Uber changes fare prices depending on demand, traffic and other factors. But it’s not necessarily good for the consumer either.
They’re not alone. Plenty of other businesses are providing “dynamic pricing” based on data they glean from your computer.
In 2012, Staples got busted charging higher prices to Internet shoppers in low-income areas. Even more interestingly, the site was measuring shoppers’ distance to competitive stores like Office Depot and giving them invisible discounts if one was near their location.
One of the industries that has most embraced dynamic pricing is travel. For a while, Orbitz was displaying higher-priced hotel rooms to Mac users, because market research showed they were willing to spend more. And a recent experiment from Digital Content Next CEO Jason Kint revealed a price discrepancy of $525 on airline tickets between different Web browsers, with Firefox as the most expensive.
What can you do about these price-setting algorithms working feverishly behind your back? Well, like any system, they have rules. Learn the rules and you learn how to exploit them. If you have access to more than one Web browser, use them both to compare prices. Check in incognito mode as well. Or run through a proxy service that redirects your traffic to somewhere else on the planet. And when you’re done, share how you got the best price with the world.