Apr 12, 2017 – from Social Intelligence

A Special Price Just for You

Coupon code on phoneLast week, President Trump signed legislation killing Internet privacy rules that would have forced ISPs to gain affirmative consent before sharing consumer data. The move puts more personal information than ever in the hands of businesses—enabling retailers not just to differentially market their goods and services but to differentially price them as well.

Enter “personalized pricing,” a business method used by information-rich retailers to maximize revenue. Personalized pricing is today being practiced on an unprecedented scale—thanks to the proliferation of personal data, the refinement of Big Data algorithms, and the widespread decline in the competitiveness of retail markets. Yet this is happening without the knowledge of the general public, whose generally negative opinion of the prac­tice (especially among Boomers and Millennials) has yet to be heard.

The passage of the ISP-favoring legislation is the latest watershed moment for personalized pricing. As we’ve mentioned before (see: “Merchants Buy Into Person­alized Pricing”), retailers are using shopper information such as age, location of residence, and Web-browsing history to adjust prices according to an individual customer’s willing­ness to buy—thereby capturing most of the available “consumer surplus.” While ISPs publicly maintain that they do not sell Web-browsing data, there is now nothing stopping them.

Personalized pricing is a powerful example of what economists call “price discrim­ination,” by which retailers segment their market and charge a different price to each segment. The mildest form (in terms of capturing consumer surplus) is “third-degree price discrimination,” by which retailers offer the same product at a discount to certain con­sumer groups—e.g., senior discounts. Then there is “second-degree price discrimination,” by which retailers offer tiered prices based on product quality (where premium options are priced far above cost) or quantity—e.g., airline ticket classes or bulk discounts. Finally comes personalized pricing, also called “first-degree price discrimination” or “perfect price discrimination” because it enables retailers to use personal data to charge the equilibrium price to each consumer.

In recent years, personalized pricing has spread extensively among e-commerce retailers—since they have access to the abundant personal data that make it possible. Orbitz has been showing higher hotel prices to Mac users since at least 2012. Same-day booking app HotelTonight recently introduced two features that show discounted rates to users based on their location. How is this possible? The instant you enter an e-tailer’s domain, the company can see everything from your browsing history to your zip code. New “fingerprinting” technology even allows vendors to track users across multiple browsers.

It’s little wonder that Amazon is able to update its prices for each cus­tomer every 10 minutes. This com­parative advantage is undoubtedly one important reason why e-commerce retail sales have doubled as a share of total retail sales since the end of the Great Recession.

But in-person retailers have been catching up. In-store analytics enables brick-and-mortar firms to learn about consumers as they navigate the store. (See: “Tracking Shoppers, Boosting Sales.”) Omnichannel shopping allows these firms to merge online and offline purchase behavior by pulling data from shoppers’ smartphones. These data are supplemented by the 3.3 billion loyalty program memberships in the United States (roughly 29 per household).

The potential revenue gains brought on by personalized pricing are impressive. Economics professor Benjamin Shiller estimates that a pricing model based on Web-browsing variables could increase Netflix’s profit by 12 percent. Consider also the added revenue from a personalized coupon campaign that increases redemption rates from 1 percent to as much as 25 percent.

Big Data and sophisticated digital IT is just one prerequisite for the spread of personalized pricing. Another is the general decline in marketplace competitiveness and transparency—and the waning of antitrust enforcement efforts. Personalized pricing cannot work without some degree of monopoly power along with widespread consumer ignorance of the practice. Otherwise, savvy consumers would buy products from a cheaper source and “arbitrage out” the difference by reselling at a markup. Monopoly power is certainly abundant in today’s economy. Look no further than the swelling market shares of leading companies in nearly every industry (see: “Shhh! The Markets Are Concen­trating”), or the steadily sliding rate of new business formation (see: “Where Have All the New Businesses Gone?”).

But personalized pricing may soon run into a populist headwind that limits its growth potential.

When consumers realize that price discrimination is occurring, they object. Most, in fact, mistakenly believe it to be illegal. A 2005 Annenberg Center study found that 64 percent of adult Internet users thought it was illegal for e-commerce sites to charge different prices to different customers—and 71 percent thought it was illegal for brick-and-mortar retailers to do so.

These concerns tend to fall along generational lines. As a general rule, older custo­mers are wary of any personalized shopping experience. Just 28 percent of Boomers would welcome a clothing store automatically selecting items for them, compared to 45 percent of Millennials. For Boomers, a retailer that knows enough to offer a different price to each individual seems intrusive.

Generation Xers, by contrast, see personalized pricing as an opportunity to get the best possible deal. These savvy shoppers know the stakes, and are likely the ones gaming the system by looking for flights from an Internet café instead of their living rooms to get lower fares—or filling online shopping carts without buying just in hope of being offered deals.

For Millennials, the story is more conflicted. On the one hand, young adults who grew up immersed in technology do not think twice about handing data over to retailers. Fully 57 percent of 18- to 24-year-olds value their personal data at $20 or less, com­pared to 41 percent of 45- to 54-year-olds. On the other hand, Millennials don’t like being “pitted” against one another because of their zip code or browsing habits.

But for now, most consumers remain largely in the dark. In fact, many companies openly price discriminate—but do so under the guise of philanthropy. Federal student aid programs enable colleges to scoop out the demand curve by offering “discounted” tuition (grants and loans) to everyday Americans who would not otherwise be able to afford it. Another example is Big Pharma: Firms routinely sell their drugs at a high list price—and then give discounts to low-income nations or individuals who can demonstrate their inability to pay the full price.

Going forward, personalized pricing will go in one of two directions. On the one hand, greater access to consumer information makes personalized pricing easier to implement. On the other hand, growing populist backlash against companies that prey on unsuspecting consumers may undermine the practice. As he does on so many issues, President Trump straddles the line: His administration and inner circle are lined with Wall Street personalities, yet he has an active populist constituency that expects him to forward its interests. On which side he and his administration ultimately step remains to be seen.

Takeaways

  • Personalized pricing, long a retail pipe dream, is now a reality. New legislation rolling back privacy regu­lations is the latest example of how ever-more consumer information is flowing into the hands of retailers. This information is invaluable to personalized pricing pro­grams designed to eliminate consumer surplus. While technological advancement opened the door for such programs, present economic conditions allow them to thrive: Personalized pricing only works in markets with low competition. However, populist consumer demands may thwart personalized pricing. Boomers and Millen­nials in particular object to privacy-invading schemes. (Xers: Not so much.)
  • Personalized pricing is designed to give deals to savvy shoppers while profiting off of others. Similar to Black Friday “sales” engineered in advance to ensure profit, personalized pricing allows retailers to mark-up items and offer discounts to savvy shop­pers. They assume that while price-sensitive customers will take the time to find the best deal, they can profit off of high earners for whom the opportunity cost of clipping coupons is too great. A price-match guarantee is one especially effective way of price-discriminating: Ohio State University researcher Matthew Corcoran found in 2012 that low-price guarantees can actually result in higher prices, since retailers figure that higher sticker prices more than make up for the (rare) price-match payout.
  • Despite popular opinion, price discrimination is legal (in most situations). When consumers detect price discrimination, most object—citing concerns over privacy and fairness. But companies are legally entitled to price-discriminate under most circumstances. The exceptions? Companies cannot alter prices based on certain protected classes (such as race, gender, or religion). Additionally, in a B2B environment, price discrimination becomes illegal under anticompetitive law (the Robinson-Patman Act of 1936) when it causes “competitive injury” to one or more entities—for ex­ample, a supplier of widgets charging less to one manufacturer, thereby giving that manufacturer a competitive advantage.
  • E-commerce sites will maintain their data advan­tage—for now. Despite the advance of omnichannel shopping and in-store analytics, it will still be a long time before brick-and-mortar retailers know as much about shoppers as e-commerce sites. Amazon changes its online prices up to 2.5 million times per day, while brick-and-mortar retailers can make only around 50,000 changes per month. As personalized pricing advances, a rising share of physical retailers will get their hands on all of this personal e-data—and add that to the in-person analytics they already possess. In time, the in-store experience could become far more personal, useful, and immersive than the e-tailer experience is today.