White House Issues Report on Big Data and Differential Pricing
Yesterday the White House released a report discussing how companies are using big data to charge different prices to different customers, a practice known as price discrimination or differential pricing. The report describes the benefits of big data for sellers and buyers alike, and concludes that many concerns raised by big data and differential pricing can be addressed by existing antidiscrimination and consumer protection laws.
Big Data and Personalized Pricing
“Big data” refers to the ability to gather large volumes of data, often from multiple sources, and use it to produce new kinds of observations, measurements, and predictions about individual consumers. Thus, big data has made it easier for sellers to target different populations with customized marketing and pricing plans.
The White House report identifies two trends driving the increased application of big data to marketing and consumer analytics. The first trend is the widespread adoption of new information technology platforms, most importantly the Internet and the smartphone. These platforms give businesses access to a wide variety of applications like search engines, maps, blogs, and music or video streaming services. In turn, these applications create new ways for businesses to interact with consumers, which produce new sources and types of data, including (1) a user’s location via mapping software; (2) their browser and search history; (3) the songs and videos they have streamed; (4) their retail purchase history; and (5) the contents of their online reviews and blog posts. Sellers can use these new types of information to make educated guesses about consumer characteristics like location, gender, and income. The second trend is the growth of the ad-supported business model, and the creation of a secondary market in consumer information. The ability to place ads that are targeted to a specific audience based on their personal characteristics makes information about consumers’ characteristics particularly valuable to businesses. This, in turn, has fostered a growing industry of data brokers and information intermediaries who buy and sell customer lists and other data used by marketers to assemble digital profiles of individual consumers.
The report notes that there is only anecdotal evidence about how businesses are using big data in the context of personalized marketing and differential pricing. This evidence suggests that sellers are using pricing practices that fall in three categories: (1) exploring the demand curve; (2) steering and differential pricing based on demographics; and (3) behavioral targeting and personalized pricing.
Exploring the Demand Curve: To learn about demand and consumer behavior, marketers often conduct demand experiments whereby they randomly assign customers to one of two possible price conditions. “These experiments are technically a form of differential pricing, since they result in different prices for different customers, even if they are ‘nondiscriminatory’ in the sense that all customers are equally likely to face the higher price.”
Steering: Steering is the practice of showing consumers products based upon their demographic group. For example, a computer company’s website might offer the same laptop to different types of buyers at different prices based upon how they self-identify (e.g., government, academic, individual, and business users) or their geographic location (e.g., as determined by their computer’s Internet address).
Behavioral Targeting and Personalized Pricing: Behavioral targeting and personalized pricing use customer-specific information to target advertisements or tailor prices for a set of products. For example, online advertisers use browsing data collected from ad networks and third party cookies to send users targeted ads. This may allow consumers to receive advertisements for products or services of interest to them. However, it may also raise concerns for consumers who may not want some kinds of information, such as visits to health or finance-related web sites, to be tracked without their consent. While behavioral targeting is widespread, there is relatively little evidence of personalized pricing online. The report posits that this may be because the methods are still being developed or because companies are slow to adopt personalized pricing or are remaining quiet, perhaps due to fears that consumers will respond negatively.
Big data involves the aggregation, sale, and use of large amounts of personal information, often in ways that are not transparent to consumers. However, the report identifies three trends that suggest that concerns about big data and personalized pricing are not stifling consumer activity on the Internet.
The first trend is the rapid growth of electronic commerce. Americans are shopping online in rapidly growing numbers, suggesting that consumers believe they are getting a good deal on the Internet, regardless of any differences in pricing practices between online and offline retailers.
The second trend is the proliferation of consumer-empowering technologies that enable them to find a better price if they are concerned about steering or differential pricing. For example, consumers frequently run searches that include the phrase “best price.” Price comparison and price-tracking sites also empower buyers to get the “best price.” The Internet has also made it easier for consumers to undermine differential pricing by becoming sellers. In particular, if a seller charges widely different prices to customers in different markets, it creates an opportunity for someone to buy the product at the low price and resell it in the high-priced market.
Finally, the report notes the relatively low adoption rates for widely available consumer privacy tools. For example, while most browsers allow users to set policies for accepting different types of cookies to track their online behavior, a test by one Internet service provider found that 96-97% of its users allow some cookies and 85-90% allow third-party cookies. According to privacy experts, this low adoption rate is because users are unaware of these tools and unaware that advertisers are gathering data about their online behavior. On the other hand, the report posits that “this could be ‘rational ignorance’ on consumers’ part, reflecting a view that the cost of engaging with details of privacy settings outweighs the benefits gained.”
The report opines that “[b]ig data clearly holds both promise and peril for the individual consumer.” While the report acknowledges that big data raises discrimination and transparency concerns, it argues that existing antidiscrimination and consumer protection laws can address these issues. However, it also stresses that “ongoing scrutiny” is necessary where companies are using sensitive information in ways that are nontransparent or fall outside the boundaries of the existing regulatory framework.
Antidiscrimination: The report argues that the efficiencies caused by big data and existing antidiscrimination laws will root out pernicious practices. With respect to using race or religion to target certain consumers, big data will provide marketers with a wide variety of behavioral data to choose from, which will make these “imperfect proxies” less useful. The Civil Rights Act of 1964 and the Fair Credit Reporting Act protect consumers in the “high-stakes markets” of credit and employment. Moreover, big data can serve as a tool to detect discriminatory practices and thus “can be used to enforce existing antidiscrimination laws more effectively, thereby obviating the need for broader restrictions on its use.”
Consumer Protection: The report relies upon Section 5 of the Federal Trade Commission Act to police differential pricing when it crosses the line into fraudulent behavior by attracting customers with false promises or burying important details in the small print. In addition, the report suggests that a way to limit unfair or inaccurate applications of big data may be to give consumers greater access to and control over their information.
This report is a continuation of the White House’s efforts to scrutinize the use of big data and discriminatory pricing on the Internet and its effects on American consumers. As we previously reported, the White House Big Data Working Group issued a Big Data Report in May 2014. The FTC also examined these issues during its September 2014 workshop on big data discrimination.