COOKIES SIGNED

Project "COOKIES" data sheet

The following table provides information about the project.

 Partnership

Take a look of project's partnership.

Map

 Project objective

Cookies (or “HTTP cookies”) enable companies to collect and exchange extensive information about users. This information is often used to improve the performance of online advertising, which website publishers rely on in order to finance the “free” content to which their users have become accustomed. Yet, the collection of information leads to a loss of privacy. Accordingly, EU policy makers have put forward initiatives to restrict cookie usage (e.g., General Data Protection Regulation (GDPR), upcoming EU ePrivacy Regulation).

So far, there exists very little empirical knowledge on the trade-off between user privacy and the economic value that website publishers, advertisers, and even users derive from cookies. As a result, policy makers have no way of telling whether their restrictions on cookies have the intended positive consequences for user privacy, or whether any benefits are outweighed by negative effects on the profits of companies—which policy makers also seek to nurture.

This proposal’s vision is to eliminate the gap in knowledge regarding the economic consequences of restrictions on the usage of cookies. I propose four work packages, each outlining the economic consequences of a specific type of restriction. In WP1-3, I will analyze a proprietary and massive (60-65 TB) set of “cookie data” that includes 472 publishers, 842 advertisers, 2.8 billion cookies and the prices of >110 billion ad impressions, that indicate the value of cookies for companies. In WP4, I collect “implementation data” to analyze the steps taken by thousands of the world’s most highly-trafficked websites to become GDPR-compliant.

My results will provide a crucial empirical foundation for cookie restrictions in an industry worth more than €10 billion per year in the EU. The required interdisciplinary research will also involve the development of novel methodologies for deriving such information from big data, and theories as to why the observed economic consequences occur.