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Yves here. Retailers intend to engage in very sneaky price discrimination. But big data is way overhyped and regularly underdelivers. It might be great at pricing airline seats, but airlines have only so many routes and run planes only so many times of day and days of the week. By contrast, the average grocery store has over 40,000 SKUs. They aren’t going to have granular enough data to discriminate finely on a lot of things. They may try to draw crude inferences, like “People who go to Starbucks daily are higher income and can/will pay more” but aside from using certain criteria to pick out less price sensitive customers, how much price gouging they might take is a crude inference. And what about stores you rarely visit, say the once a year at best sports store shopper?
In addition, this type of price discrimination is against the law in many cities which require merchants to post prices and honor them. But the threat of this sort of system is an argument in favor of not using ApplePay and other phone-based payment systems, which could provide even more granular info about your shopping habits, or not using a smart phone, or putting it in a mini Faraday cage when you are going on a serious shopping mission. Plus if this sort of system starts to be implemented, it’s not hard to imagine that software developers would implement apps to block inquiries from purchase snooping systems, or better yet, feed them incorrect data that says you are price sensitive (like a false history of shopping regularly at discounters).
By David Morris, co-founder of the Institute for Local Self-Reliance who directs its initiative on The Public Good. He is the author of “New City States” and four other non-fiction books. Follow him on Twitter: @PublicMorris. Originally published at Alternet
In the beginning there were no fixed prices. Every transaction involved a negotiation between buyer and seller. Then in 1861, as Guardian reporter Tim Adams informs us, Philadelphia retailer John Wanamaker introduced price tags, along with the slogan, “If everyone was equal before God, then everyone would be equal before price.” Wanamaker’s stated intent was to establish “new, fair and most agreeable relations between the buyer and the seller.”
For the next 150 years, fixed pricing became the norm. Companies determined prices either by pegging them to those of their competitors or by calculating the cost of a good or service and adding a profit, with an occasional white sale or going-out-of-business sale, or discounted day-old bread.
In the 1990s came the internet, and in the 2000s, online shopping and smartphones. Prices could be changed remotely and frequently. Initially businesses changed their prices largely to take advantage of a shortage of supply (e.g. Uber with its surge pricing) or an increased demand (airlines, in essence, auctioning off tickets to last-minute customers).
Big data emerged and with it the ability for businesses to know their customers in a most intimate and detailed fashion. Initially, sophisticated algorithms allowed businesses to individualize ads. Now as they’ve gathered even more of our personal data they’ve begun to individualize prices. As Adams notes, the travel site Orbitz calculated that Apple Mac users would pay 20-30 percent more for hotel rooms than users of other brands of computer and adjusted its pricing accordingly. Jerry Useem in the Atlantic maintains the price of Google’s headphones may depend on how budget-conscious our web buying history reveals.
Electronic price tags may soon allow dynamic pricing in brick and mortar stores. Such tags are already in stores in France and Germany and parts of Scandinavia.
The Guardian reports that B&Q, the largest home improvement and garden center retailer in the UK and Ireland, has tested electronic price tags that could change the price of an item, based on which customer is looking at it, something it can derive from the Wi-Fi connection to the customer’s mobile phone. Not yet in stores, but that may be just a matter of time.
Dynamic pricing strives to maximize the seller’s profit by raising the average price he receives. Economists believe that is simply good business tactics. The rest of us remain unconvinced.
We don’t like being taken advantage of. More than half the states have anti-scalping laws, a response to brokers buying up thousands of concert tickets, shrinking supply, and allowing them to charge concert goers far more than the face value of the ticket. Last year Congress got into the act, passing a law that makes it illegal for brokers to use software that bypasses online systems designed to limit the number of tickets an individual can purchase. But these laws target only a small slice of the retail sector and aren’t vigorously enforced.
We’ve also taken action to stop sellers from taking advantage of a scarcity imposed by natural disasters to charge exorbitant prices to desperate customers. Over 30 states have enacted laws against such price gouging.
But as Ramsi Woodcock, professor of legal studies at Georgia State University, observes, those outraged by Delta’s reportedly asking $3,200 for a ticket out of Florida as Hurricane Irma approached should be aware that dynamic pricing enabled Delta to charge the same price to last minute customers two weeks before.
We’ve imposed no limits on dynamic pricing, although we’re nibbling around the edges of imposing some constraints on the sale of our personal data. Woodcock believes dynamic pricing could have anti-trust implications. Anti-trust is justified by many as a way to stop or break up monopolies that could artificially raise prices and reduce total consumer welfare. In a detailed article, Woodcock argues that big data enables “price discrimination (that) extracts more value from consumers than uniform pricing, by tailoring price to the maximum level tolerated by each consumer.” And thus warrants anti-trust enforcement.