White House Releases Report on “Big Data and Differential Pricing”

According to the report, Big Data has lowered the costs of collecting customer-level information, which has encouraged a shift from price discrimination based on broad demographic categories (e.g. senior pricing for movie tickets) towards personalized pricing that may change for each consumer (e.g. airline tickets).  Additionally, the increased availability of behavioral data is helping drive new pricing strategies.  After briefly discussing benefits and drawbacks of differential pricing, the report concluded that “whether differential pricing helps or harms the average consumer depends on how and where it is used.”

Notably, the report finds that there is relatively little evidence of personalized pricing on the Internet.  It notes that a 2014 Northeastern University study found no evidence of personalization based on user-specific information at any of the 10 general merchandise web sites in the study and could only discern behavioral discrimination at 1 out of 5 travel sites.  Similarly, the report highlighted the fact that recent studies of the data broker industry published by the Federal Trade Commission (FTC) and Government Accountability Office (GAO) contained no specific references to examples of personalized pricing.  The White House report comments that “the relative scarcity of personalized pricing examples suggests that companies are moving slowly or remaining quiet, perhaps due to fears that consumers will respond negatively, but also because the methods are still being developed.…”

The report next discusses three trends that suggest that Big Data and personalized pricing are not stifling consumer activity on the Internet.  First, e-commerce has significantly grown in the last decade.  Second, consumers increasingly have a variety of tools such as price comparison websites to help them find a better price if they are concerned about differential pricing.  Third, consumers have not widely adopted privacy tools.

Nevertheless, the report finds that the combination of Big Data and differential pricing does raise serious concerns.   For instance, the report finds concerning the use of differential pricing when implemented through complex or opaque pricing schemes designed to screen out unsophisticated buyers.  The report also calls out the potential for discrimination or fraudulent behavior in this space.  It recommends the use of existing antidiscrimination statutes and the Federal Trade Commission act to policies these activities.

Finally, the report suggests that one way to limit unfair or inaccurate applications of Big Data might be to give consumers greater control over their information.  The report again points to the FTC and GAO reports as examples. These reports suggested the need to rethink existing frameworks for regulating consumer privacy and the acquisition and use of Big Data in the marketing context.

Many businesses will be relieved to find this report does not suggest the need for new legislation to regulate differential pricing.  Also, while the report points out the potential for abuse, little evidence is shown that would serve as the basis for calls for new regulation.  We will be monitoring reaction to the report by legislators and advocates and will provide an update should differential pricing rules gain traction in the Administration or the Congress.

Authored by the HL Chronicle of Data Protection Team