Imagine this: You buy a pair of shoes from a popular online retailer. Across town, another shopper buys the exact same pair of shoes from the same retailer. Except he paid $10 less than you did. Not because he used a coupon or discount code, but because the store decided to offer him a lower price than you.
Sound unfair? Maybe. But it’s an example of the kind of experience that could become more common as retailers experiment with personalized pricing, or tailoring prices based on information they’ve gathered about you like your browsing history, purchase history, and your zip code.
Truly personalized pricing – or first-degree price discrimination – is more theory than reality at this point, at least when it comes to online shopping. Yet retailers are starting to look at ways to use big data to squeeze more out of shoppers, either by charging some people more or by offering targeted discounts to people who might not otherwise click “buy.”
Of course, personalized pricing is nothing new. Any time you haggle with someone over a price, whether you’re negotiating at a garage sale or the car dealership, you end up with a price that’s specifically tailored to you. Many other businesses practice a different and widely accepted kind of price discrimination by charging certain customers more (like Tinder setting a higher price for older users) or offering discounts to some (think “early bird” dinner specials targeted toward seniors).
Most people accept that kind of semi-personalized pricing because it’s fairly transparent. If you want to get the deal on dinner, you need to be willing eat at 4 p.m. If you want a better price on a used car, you have to be willing to haggle. But the coming wave of personalized pricing will likely be harder for consumer to see, making it difficult for someone to know if they’re really getting the best deal. That has some concerned, including the White House, which released a report in early 2015 that warned that personalized pricing might lead to discrimination and fraud.
Retailers are already scooping up all kinds information about your browsing and shopping habits and using it to send you special discounts. Many supermarket chains track the purchases of people who participate in store loyalty programs and then use that information to send them personalized coupons. This kind of targeted pricing can increase sales and also make it harder for competitors to compete on price, since they can’t easily see what deals are being offered to shoppers, per a report in Bloomberg.
Personalized coupons for milk and bread are just the tip of the iceberg, though. Experts predict that retailers will eventually start using the mountains of data they’ve accumulated to customize the prices customers are initially offered when they shop. Soon, the day may come when the price you see while shopping online for a sweater or book may not be the same as what your neighbor across the street sees.
“They may be talking about it more than they are implementing yet,” said Joseph Turow, a professor at the University of Pennsylvania’s Annenberg School for Communication, in an interview with the Business of Fashion. “But the general notion is that the way to make money online is to target people with different prices based upon their proclivities, based upon their interests.”
If that sounds a little creepy to you — and perhaps not quite fair — you’re not alone. Turow conducted a study that found that more than three-quarters of people would be bothered if they found out that other people were paying less than they were for the same products.
“We have found that Americans aren’t crazy about the idea by any means. But in general, I think companies are more interested in this than general shoppers are,” said Turow.
Fear of customer backlash is likely giving companies that are interested in exploring personalized pricing pause. Orbitz received some flak back in 2012 when a Wall Street Journal report revealed that it was showing Mac users more expensive hotel rooms. Orbitz’s data indicated Apple fans tended to spend more on travel than Windows users. When Amazon tried charging shoppers different prices for the same DVD in 2000, customers made their objections clear. CEO Jeff Bezos called the experiment “a mistake” and refunded money to people who were charged more.
Yet those missteps haven’t completely stopped retailers from trying out personalized pricing. Pure, a San Francisco-based cosmetics company, has tried offering bigger discounts to customers who an algorithm predicts are more likely to leave the site without making a purchase, according to a report in Forbes.
In 2014, researchers at Northeastern University found that people visiting the websites of major retailers like Home Depot, Sears, and, yes, Orbitz, sometimes saw different prices or were shown different products depending on what browser or device they were using, or whether they were logged into an account with the store.
Savvy and motivated shoppers may be able to find the best deals by using private browsing settings when shopping online, said Christo Wilson, the computer science professor who conducted the study, in an article for the Washington Post. He also had some words of advice for retailers considering personalized pricing: “Rather than using opaque and creepy algorithms to secretly alter content, companies could stick to the kinds of real-world incentives that shoppers already know and love, like coupons and sales.”