By Johnson Fu
Personal information holds economic value incentivizing private companies to collect information on customers. Many businesses—from grocery chains, to investment banks, to the United States Postal Service—employ a “predictive analytics” department that investigates a consumer’s shopping habits in order to uncover information they then use to target their advertising.[1] But problematic in this context is both the concern of autonomy over personal data and the latent power to expose such meaning–willingly, or not. As proof, the recent Equifax data breach compromised the personal information of over 145 million Americans.[2] Uber hailed a similar ride when it withheld, for over a year, that infiltrators had breached their systems and hijacked data identifying 57 million persons.[3] Yet, “[p]eople tend to click OK [on] almost any request they see pop up on their screens. This is all the more true when firms make the use of a service conditional on the user’s consent.”[4]
The recent Equifax data breach compromised the personal information of over 145 million Americans. Uber hailed a similar ride when it withheld, for over a year, that infiltrators had breached their systems and hijacked data identifying 57 million persons. Yet, “[p]eople tend to click OK [on] almost any request they see pop up on their screens. This is all the more true when firms make the use of a service conditional on the user’s consent.”
Understanding the value of data and the risks involved in providing personal data, therefore, will not only prevent and reduce the risk of identity theft, but it will also alert consumers to the multiple approaches for valuing personal information.[5] There is first the issue of measuring the value of one’s personal data in return for getting access to discounts and services. The privacy inherent in personal data is often arbitrarily construed against the value of other desirable goods or services. As such, a consumer may not properly understand how to value their personal information.[6]
Data valuation focusing only on monetary value does not encompass all the necessary measures of value. Perhaps unsurprisingly, a discussion of the value of personal data is incomplete without recognizing the increased risk of identity theft, privacy loss, and the fact that personal data can be easily resold.[7] Moreover, the size, completeness, and particularities of dataset characteristics all are at the heart of finding a practical way to assign value to personal data in the digital landscape. In fact, datasets that disclose more sensitive and personal characteristics carry greater demand and price.[8]
A practical model for the valuation of data as an asset is to consider how much corporations profit from our personal information. There is a case to argue that if consumer data was efficiently and transparently priced as an asset, “consumers would be less likely to provide the advertisers, data brokers, and tech giants that dominate the personal data economy the nearly unfettered access to the information that they now enjoy.”[9] In 2016, Facebook generated over $26 billion in advertising revenue, which amounts to approximately $20 per monthly active user.[10] Facebook, therefore, accounted for 19.7% of the 2016 US Digital Advertising industry’s total $87 billion of revenue.[11] As a result, the “average U.S. consumer can make $240 per year monetizing their data for digital advertising.”[12]
Another approach to valuing personal information is to consider its value through the eyes of the shareholder. “In other words, personal data is worth whatever the shareholder is willing to pay to acquire client data from a data-centric company, as was the case when WhatsApp and Instagram were acquired by Facebook, for instance.”[13] The richer and more thorough the information a company has, the more money it can make from the users’ activity, which in turn increases a company’s valuation. Applying this formula, Facebook decisively acquired WhatsApp for $19 billion; “that is, to pay $30 for each of its 600 million users. Similarly, [it] also paid $30 for each of the 33 million Instagram users back in 2012.”[14]
Ultimately, the value of personal information pivots on many factors that each independently influence its valuation. These factors include both the context in which the personal data was collected and the purposes for which the personal data is used. On the one hand, holding more information enables enterprises that retarget their advertisements to consumers–benefiting both the firm and customers whom enjoy behavioral targeting. On the other hand, “[s]urveys show that most people do not want [behaviorally] targeted advertising, because they find it creepy or privacy-invasive.”[15]
Altogether, knowing the value of their personal data would effectively empower these people to achieve ownership of their data that ultimately increases or diminishes in value according to the way it is managed. But determining the valuation of personal data involves several problems–many of which are significant and without mitigating solutions. Once these practical problems are solved, consumers will begin to fully appreciate the value of the personal information they have been providing to private enterprises that currently exploit this important resource.
[1] Charles Duhigg, How Companies Learn Your Secrets, N.Y. Times: N.Y. Times Mag. (Feb. 16, 2012), https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all.
[2] Algorithms: How Companies’ Decisions About Data and Content Impact Consumers: Hearing Before the Subcomm. on Commc’ns. and Tech. and the Subcomm. on Dig. Commerce and Consumer Prot. of the H. Comm. on Energy and Commerce, 115th Cong. 4 (2017) (statement of Michael Kearns, Professor and National Center Chair, Department of Computer and Information Science at the University of Pennsylvania).
[3] Eric Newcomber, Uber Paid Hackers to Delete Stolen Data on 57 Million People, Bloomberg (Nov. 21, 2017, 7:21 PM), https://www.bloomberg.com/news/articles/2017-11-21/uber-concealed-cyberattack-that-exposed-57-million-people-s-data.
[4] F. Zuiderveen Borgesius, Behavioural Sciences and the Regulation of Privacy on the Internet, in Nudge and the Law: A European Perspective 179, 180 (Alberto Alemanno & Anne-Lise Sibony eds. 2015).
[5] Sasha Romanosky & Alessandro Acquisti, Privacy Costs and Personal Data Protection: Economic and Legal Perspectives, 24 Berkeley Tech. L.J. 1061, 1063 (2009).
[6] Id.
[7] Brian Stack, Here’s How Much Your Personal Information Is Selling for on the Dark Web, Experian (Apr. 9, 2018), https://www.experian.com/blogs/ask-experian/heres-how-much-your-personal-information-is-selling-for-on-the-dark-web/.
[8] Id.
[9] How Much Is Your Data Worth? At Least $240 per Year. Likely Much More, Medium: Wibson, https://medium.com/wibson/how-much-is-your-data-worth-at-least-240-per-year-likely-much-more-984e250c2ffa (last visited Oct. 14, 2018).
[10] Id.
[11] Id.
[12] Id.
[13] Pauline Glikman & Nicolas Glady, What’s the Value of Your Data, TechCrunch (Oct. 13, 2015), https://techcrunch.com/2015/10/13/whats-the-value-of-your-data/.
[14] Id.
[15] Borgesius, supra note 4, at 182.
