When discussing the traditional advertisement market in previous posts, I touched on the history of data collection by companies like Nielsen, who sold it to radio and television networks to negotiate advertisement rates. These rates were traditionally high enough that they were reserved for large businesses with big budgets.
In the early days of the internet, the fixed costs and the trade-offs in terms of reach and conversion that resulted from the higher rates of highly segmented and targeted advertisement, made behavioral advertisement only available to very few players in the industry, representing a small portion of the online advertisement market (Evans, 2009).
The technological advances provided by the internet, have increased the volume, accuracy and detail of personal information that content producers can gather. Furthermore, these developments have made data collection, selling and advertisement online accessible and easy to just about any person with some basic web literacy.
In this new landscape of online advertisement, every website owner has now access to collect very detailed information about their visitors, and through networks like DoubleClick and AdSense owned by Google, use this information to monetize their content. Furthermore, any person can make use of Google or Facebook’s advertisement networks to serve advertisement to a very specific group of people for small sums of money.
Not only has the evolution of technology made data more accessible, more detailed and more accurate, but also the fact that nowadays nearly every device is constantly gathering data, how ubiquitous social media is and the rapid expansion of IoT, has resulted in a tremendous volume of data being produced and gathered at any given moment, and increasing exponentially.
While the volume of data produced every year is increasing exponentially, its value is also increasing, and data has become of of vital economic value to business, government, and society.
Bergemann & Bonatti (2015) provide an assessment from the standpoint of economic theory of the different actors, selling and buying models and price points for these user data. And the emerging field of data mining has shown how managing and interpreting this data to gain insight is now seen as a key competitive advantage.
Many organizations today, are building their business around their ability to collect and analyze information to extract business knowledge and insight (Eastin et al., 2016), not unlike what Nielsen did for TV ratings, but at a significantly larger scale.
Data has become a factor just as important to production as labor, capital, and land in value creation, with the greatest concentration of money taking place at data-integration junctions, with the user as the primary source of value generation (Eastin et al., 2016).
In this new landscape of the data economy, the old model of “selling eyeballs” takes on a whole new meaning. While advertisement as a form of financing content creation has existed for centuries, never before had the data collected about audiences been so large, so thorough and ultimately so valuable.
The two sided market is now full of so-called pay-with-data transactions, occur whenever someone visits a website to obtain a product or service, either for free or for a fee, and allow the use of their personal data as a form of payment (Warner & Sloan, 2012). This dynamic raises concerns regarding privacy, ownership and profiting from personal data and businesses vs consumer interests in an asymmetric market (Nissenbaum, 2011).
- Bergemann, D., & Bonatti, A. (2015). Selling Cookies. American Economic Journal. Microeconomics, 7(3), 259–294. https://doi.org/10.1257/mic.20140155
- Eastin, M. S., Brinson, N. H., Doorey, A., & Wilcox, G. (2016). Living in a big data world: Predicting mobile commerce activity through privacy concerns. Computers in Human Behavior, 58, 214–220. https://doi.org/10.1016/j.chb.2015.12.050
- Evans, D. S. (2009). The Online Advertising Industry: Economics, Evolution, and Privacy. The Journal of Economic Perspectives, 23(3), 37–60. https://doi.org/10.1257/jep.23.3.37
- Nissenbaum, H. (2011). A Contextual Approach to Privacy Online. Daedalus (Cambridge, Mass.), 140(4), 32–48. https://doi.org/10.1162/DAED_a_00113
- Warner, R., & Sloan, R. H. (2012). Behavioral advertising: from “One-Sided Chicken” to informational norms. Vanderbilt Journal of Entertainment and Technology Law, 15(1), 49–.
Note: The content of this blog post was written as part of the process of writing my thesis’ theoretical background, as a way to organize my ideas and clean them up in writing. The posts were temporarily taken down to prioritize the academic work’s originality, and have been reinstated after the publication of the thesis in the Swedish registry.