Fashion companies routinely tap personal data to tailor promotions and special offers to individual consumers. The same information can now be used to personalise pricing.
Istanbul’s Grand Bazaar | Source: Shutterstock
LONDON, United Kingdom — Personalised pricing is as old as commerce itself. A market stall owner sizes up a prospective customer based on a wide range of signals — such as how she speaks and dresses — then offers her a special price: “For you, ten dollars.”
Today, consumers are more used to standardized pricing and the ‘law of one price’ generally prevails, based on the logic that differences between prices for the same good are eliminated by market participants taking advantage of arbitrage opportunities. Indeed, so the theory goes, when a product is sold via multiple channels, the cost should not vary by more than the differences in shipping, taxation and distribution costs. If it does, with a huge range of retailers to choose from, customers will simply shop elsewhere.
Nonetheless, some online retailers are returning to the tactics of the bazaar, leveraging the data trails generated by Internet users to set different prices for different customers.Just like the seller at a market stall, e-tailers can now ‘size up’ each customer that visits their site. “Every retailer, once you get to their website, they know where you are from because of your IP address. And they know that to the accuracy of a ZIP code, so they can know that you are from a more affluent area, for example,” said Hana Ben-Shabat, partner for the Americas at A.T. Kearney, a global consulting firm.
“The way to make money online is to target people with different prices based upon their proclivities, based upon their interests.”
This, combined with cookies, can tell a company a significant amount about individual customers, including some of the websites they have visited, how regularly and for how long; which products they inspect and purchase. In addition, cookies store information that customers volunteer in online forms — for example, shipping address and other profile data. Based on this kind of data, it’s possible for retailers to predict what products a consumer is interested in buying, when they are likely to buy them and, critically, the price they would be willing to pay.
Currently, a wide range of retailers use this kind of data to target individual shoppers with personalised offers and promotions. “But the same mechanism that allows retailers to give customised offers to you — that’s the same mechanism that could allow them to determine differentiated pricing,” said Ben-Shabat. “In theory, e-commerce makes it really easy to change prices, because you just have to go in the system and change it. You don’t have to go into 2,000 shelves in 2,000 stores to change the price.”
“Everybody’s talking about this,” said Professor Joseph Turow, of the University of Pennsylvania’s Annenberg School for Communication. “They may be talking about it more than they are implementing yet… 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.”
In theory, charging all consumers the same price is ineffective, because some of those consumers would have been willing to pay more, while others who opted not to buy would have responded to a lower price. Personalised pricing, so the economic theory goes, can save companies this lost revenue. By analysing customer data, a retailer can work out a customer’s “reservation price” — the maximum amount they would be willing to pay for a specific product, before they had “reservations” about buying it — and then charge them that amount.
Back in 2000, Amazon was found to be charging its regular consumers higher prices for some products, after one shopper deleted the cookies on his computer that identified him as a regular Amazon customer and saw the price of a DVD drop. The company, which put the differences in price down to a “random price test,” refunded customers who had paid higher prices and Amazon CEO Jeff Bezos said the company “never will test prices based on customer demographics.”
In 2012, a Wall Street Journal investigation found that companies including Staples, Rosetta Stone and Home Depot were showing customers different prices based on “a range of characteristics that could be discovered about the user.” Staples, for example, showed different prices to customers after estimating their locations and working out how close the person was to a competitor’s brick-and-mortar store. In this instance, customers in locations with a higher average income were generally shown lower prices.
Also in 2012, The New York Times reported that supermarket chain Safeway was experimenting with a personalisation programme that created customised product offers for individual consumers. At the time, the company said it also had the capability to adjust prices based on consumer habits and was considering leveraging this.
Firms such as Wiser, Dunnhumby and Blue Yonder offer software and data solutions to retailers that employ “dynamic pricing,” whereby prices change over time in response to forces such as inventory, demand or the prices displayed by competitors. Travel sites are a prime example. Do these firms also enable their clients to simultaneously charge customers different prices for the same product?
“Technically, the answer would be yes we can absolutely do that,” said Rakesh Harji, UK Managing Director for Blue Yonder. “We can absolutely optimise the price according to not only the region, but according to the channel in which the consumer is actually interacting with the retailer.” For example, a shopper using a mobile device can be charged a higher price than a customer using a desktop computer. But, according to Harji, Blue Yonder’s clients do not currently practice personalised pricing.
“Most companies, on a purely person-specific, price online basis, are hesitant, I think with good reason,” said Craig Zawada, chief visionary officer at PROS, a software company that offers price optimisation solutions. “It remains to be seen whether consumers would accept that.”
Charging different prices to different people is legal in the United States (unless it is done on the grounds of race, gender or other discriminatory characteristics). Yet a 2005 survey co-authored by Professor Turow found that 64 percent of the American adults surveyed did not know that it was legal for “an online store to charge different people different prices at the same time of day.” In addition, 76 percent agreed that “it would bother me to learn that other people pay less than I do for the same products.”
“I’ve spoken to some executives about this in the last couple of months and the fear that they have is that people will find out about it and get angry,”
said Professor Turow. “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.”
“I think it harms consumers from the perspective of privacy,” added Ryan Calo, assistant professor of Law at the Univeristy of Washington’s School of Law, whose work specialises in law in digital markets. “People don’t understand that their reservation price is being hit on the basis of the data about them. People don’t realise that by giving up information about themselves they are getting a worse deal.… I think that consumers, when they hear about it, are not happy about it. Companies that have tried to do it they have got some pretty serious push-back.”
It’s not easy for consumers to detect when they are being targeted with personalised prices. Nikolaos Laoutaris has co-authored reports on price discrimination in e-commerce and is the creator of ‘Sheriff’, a piece of software that can detect when a website is offering different prices to customers based in different locations.“From different browsers, different computers that belong to different people in the same location, we saw differences on the price,” he said. “But we cannot yet say that if you visit website X, Y, or Z and they think that you are above thirty years old, you are going to pay more or less. It’s very difficult to do that because you need a lot of data to establish those correlations.”
A demonstration of Sheriff on the Luisa Via Roma website showed that Dolce and Gabbana’s medium reptile-skin ‘Sicily’ bag would appear to cost €4,665.00 to a customer based in Israel, but €6,622.00 to a shopper in Massachusetts. “We see the pricing, but we cannot yet decode it and understand why it happens,” said Laoutaris.
There are no known cases of fashion companies implementing individualised pricing online. But for luxury brands in particular, leveraging personalised pricing could be damaging as it throws into question the intrinsic value of their goods. Brands like Louis Vuitton do not discount their products, so as not to undermine consumer perception of their value.
Yet the luxury fashion industry has long charged customers in different countries different prices for the same goods and is used to the idea of treating different segments of customers differently via personalised promotions, VIP discounts, exclusive sales and other tactics.
Is personalised pricing next?
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