Advertisement Tracking in Modern Days

Jinghan Li

It is a common experience: when you scroll through Instagram, the sponsored advertisement among your following posts is something you searched on Google one hour ago. To be honest with yourself, how do you feel about these targeted ads? Do you have a triggered interest for purchase? How those apps track and share your search preference and determine your possible interested content? In this blog post, I will introduce the mechanism of individualized ads, the purpose of those ads, and the general public response about the personalized ads. Hopefully, after reading, you will learn about the core concept of digital advertising and will not be scared when you see targeted content again. 

The personalized advertisement we encounter every day is a result of “digital advertising,” also known as “Internet advertising,” and serves as a determining factor for monetization of various Internet services (Chen 2016). Many IT companies with scales in the world, such as Google, are highly involved in digital advertising to generate large revenues that support its free search engine services (Chen 2016). The revenue, as many of us may imagine, is tremendous. With a wider use of mobile devices since 2012, mobile advertising has become a favourite platform for advertisers. Global revenue of mobile advertising achieved an outstanding 92% growth from 2012 ($10B) to 2013 ($19.3B) (Chen 2016). The ecosystem of digital advertising consists of users (us!), publishers, advertisers, and brokers (Mellet 2020). Here, the publishers refer to the organizations trying to increase its monetization through involvement in Internet advertising, which is commonly the tech companies such as Google and Instagram as introduced above. Those tech companies provide platforms to place those ads, and they collect revenue from the advertisers who are willing to pay for those spots (Mellet 2020). We may imagine that the advertisers and publishers may sit together, negotiate about the payment and terms, and then sign the contract in a meeting room. However, this is not the case for a great majority of advertisements we see today. Brokers, with sub-categories of ad-network and ad-exchanges, make those decisions perform online within seconds (Mellet 2020). 

One example of the online negotiation process is real-time-bidding (RTB) through ad-exchanges (Cook 2020). Under these mechanisms, publishers and advertisers share their tracked data of the users in order to expand their knowledge of the user and find a better match between the publisher and the advertisers. In fact, the bidding behavior is heavily influenced by the data tracking techniques, and one research team observes through machine learning that different tracking tools can present the same user with a different persona, thus resulting in different ads presented on that user’s web browsing page (Cook 2020). Many people are concerned about this massive sharing of data, so there has been some proposed softwares to block ads and data tracking, such as EasyList and EasyPrivacy, which are widely considered to be the most stringent methods (Cook 2020). Some researchers also investigate whether this data tracking happens on the client-side or the server-side. The results show that most sharing occurs on the server side, so client side blocking techniques cannot effectively stop the sharing. Another research team tested upon those strategies, and found even under the most realistic conditions, those blocking tools can still leak 40-80% of user data to publishers and advertisers (Bashir 2018). 

After all those discussions of advertisers, brokers, and publishers, we all realized  one silent party is the users. In fact, there has been a reported gap between the user and publisher’s impression on personalized advertising. A Wall Street Journal showed 72% felt being offended when they see targeted advertisements while browsing the Internet. Another survey showed 66% of Americans felt negative about how marketers track their data to generate individualized information. In another survey, 52% of respondents would like to turn off behavioral advertising (Cook 2020). In the 1990s, two ethical questions were raised: whether it is ethical for a company to acquire and store individual information without explicit consent, and whether it is ethical to disclose information about individuals without explicit consent (Martin 2016). Those questions, with great values in constructing a safe and welcoming space for user privacy, are sadly being avoided by the marketers and directly employ their power in tracking. There are many recent lawsuits and regulations targeting user consents in data sharing, and hopefully in the near future we can resolve the two questions above. 


Citations

  1. Chen, G., Cox, J. H., Uluagac, A. S., & Copeland, J. A. (2016). In-Depth Survey of Digital Advertising Technologies. IEEE Communications Surveys & Tutorials, 18(3), 2124-2148. doi:10.1109/comst.2016.2519912

  2. Mellet, Kevin and Thomas Beauvisage. 2019. “Cookie Monsters. Anatomy of a Digital Market Infrastructure.” Consumption Markets & Culture 23(2):110–29. Retrieved (https://www-tandfonline-com.libproxy.berkeley.edu/doi/pdf/10.1080/10253866.2019.1661246?needAccess=true). 

  3. Bashir, Muhammad Ahmad and Christo Wilson. 2018. “Diffusion of User Tracking Data in the Online Advertising Ecosystem.” Proceedings on Privacy Enhancing Technologies 2018(4):85–103. Retrieved (https://doaj.org/article/b3164f51c8c340609a71df172f6ca16a).

  4. Cook, John, Rishab Nithyanand, and Zubair Shafiq. 2020. “Inferring Tracker-Advertiser Relationships in the Online Advertising Ecosystem Using Header Bidding.” Proceedings on Privacy Enhancing Technologies 2020(1):65–82. Retrieved ( https://doaj.org/article/766b6a88a7804f39b66dee9b6c9f6cca)

  5. Koop, Martin, Erik Tews, and Stefan Katzenbeisser. 2020. “In-Depth Evaluation of Redirect Tracking and Link Usage.” Proceedings on Privacy Enhancing Technologies 2020(4):394–413. Retrieved (https://doaj.org/article/1e4403cbcd8141e792fac8c5f8ee2f8a).