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Cookie Wars: How New Data Profiling and Targeting Techniques Threaten Citizens and Consumers in the “Big Data” Era

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Abstract

Digital marketers have unleashed powerful and far-reaching data collection, profiling, and targeting technologies online, incorporating the latest developments in such fields as semantics, artificial intelligence, auction theory, social network analysis, data mining, and neuroscience. Consumers and policymakers, however, are largely unaware of how online advertising operates nor are they prepared to assess the impact of tracking technologies that monitor our travels on the Internet and generate information for digital targeting profiles. Unlike more traditional advertising, digital marketing watches us, relying on such techniques as data optimization, “self-tuning” algorithms, “intent” data, and “immersive” multimedia to enable personalized, highly targeted marketing. Such marketing has also been integrated into the core business models of social networks, mobile communications, gaming platforms, virtual worlds, and online video. With the repeated failure of industry self-regulation, strong privacy safeguards are urgently needed, including provisions that will fully apprise consumers of the privacy implications of contemporary digital data collection practices.

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Notes

  1. 1.

    See also eXelate Networks, “Targeting Exchange, Digiday 2009” http://www.slideshare.net/DM 2EVENTS/exelate-networks-1556802 (viewed 23 Mar. 2011).

  2. 2.

    Sociomantic Labs, “Social Targeting,” http://www.sociomantic.com/social-targeting.

  3. 3.

    Samira Lama, “Lennox Invests in a Mobile Strategy and Sees Lower Cost per Conversions,” Google Mobile Ads Blog, 1 July 2011, http://googlemobileads.blogspot.com/2011/07/lennox-invests-in-mobile-strategy-and.html;; Neurosense, “Applications,” http://www.neurosense.com/apps.html (all viewed 5 July 2011).

  4. 4.

    See also “Advertising Research Foundation Develops Standards for Neuromarketing Research,” 22 Mar 2011, http://www.prnewswire.com/news-releases/advertising-research-foundation-develops-standards-for-neuromarketing-research-118423879.html (viewed 23 Mar. 2011); A. K. Pradeep, The Buying Brain (Hoboken, NJ: Wiley, 2010).

  5. 5.

    In its joint academic grant program operated with ad giant WPP, Google supports scholars who can help make interactive ads more precise. For example, in a recent research round, Google listed as “Topics of interest” that included: What do we know and what more do we need to know about on-line audiences? How can advertisers be welcome in social networks? How do teens interact with digital media and what are the implications? How can pharmaceutical brands engage more effectively online? What are the unique marketing and targeting opportunities for other verticals: financial services, insurance?.

  6. 6.

    See also Yahoo, “Behavioural Targeting,” http://advertisingcentral.yahoo.com/en_GB/products/behaviouraltargeting (viewed 23 Mar. 2011).

  7. 7.

    Yahoo, “Yahoo! Smart Ads,” http://advertisingcentral.yahoo.com/en_GB/products/retargeting_smartads (viewed 23 Mar. 2011).

  8. 8.

    Teracent, “Advertiser Solutions,” http://www.teracent.com/advertiser-solutions/ (viewed 23 Mar. 2011).

  9. 9.

    For an example of eye-tracking, see Enquiro (2011).

  10. 10.

    See also Media Innovation Group, http://www.themig.com/mobile/zap.php (both viewed 15 Feb. 2011).

  11. 11.

    Other ad giants operating their own data platforms or “audience buying” services include Havas (Adnetick), IPG (Cadreon), and Publicis (VivaKi). VivaKi, http://www.vivaki.com/ (all viewed 23 Mar. 2011). In November 2010, Google extended its digital ad targeting partnership with agency giant Publicis and its “VivaKi Nerve Center Trading Desk.” They are buying video and mobile ads via Google Doubleclick’s ad exchange for data targeting.

  12. 12.

    Ebbert, “eXelate CEO Zagorski Discusses New DataLinX Platform and Company Strategy.”

  13. 13.

    As Econsultancy describes it, a demand-side platform includes: Connects to multiple inventory sources (e.g., ad exchanges, optimizers), creating a significant pool of impressions; Calculates the value of an impression relative to its characteristics in real-time; Makes decisions on what impressions to bid for and what price to bid for each in real-time; Enables data integration with third-party data providers, agencies, analytics companies and clients; Integrates data, targeting, optimization, analytics, impression attribution, and reporting; Makes the media and data buying process more transparent and efficient; Enables media buyers to manage and optimize their campaigns in real-time though a single interface; Provides better insight into users’ behavior and allows retargeting across numerous platforms.

  14. 14.

    In deciding which advanced online targeting technology company to use, marketers are told they should ask themselves a range of data-related questions, including “Who are their data partners? Is the company able to integrate and manage first-party data as well as third-party data sources? Can you use data from any third-party provider or are you limited to certain providers only? What types of data can the platform integrate, e.g., intent data, unique personal data? Does the platform have predictive targeting… capabilities? Are cross-platform buying capabilities (e.g., Facebook, Google Adwords) offered?” Questions that should be asked on “targeting and optimization” include “Is the optimization approach rules-based or algorithmic-based? Are the algorithms static or dynamic? Does the DSP offer real-time assessment, page-level optimization and automated optimization? …What targeting approaches does the DSP offer (e.g., demographic, contextual, behavioral, geo-targeting, retargeting, multivariate targeting)?” Econsultancy, “Demand-Side Platforms Buyer’s Guide,” (p. 33).

  15. 15.

    http://www.bluekai.com/intentdata_bluekaiinside.php (both viewed 9 Feb. 2011).

  16. 16.

    How does eXelate collect all these data? As it explains, “All of eXelate’s online-based activity data is directly sourced from online publisher partners via tags located on web pages in which consumers interact with relevant content or queries. Via this tag, eXelate is able to drop a ‘targeting cookie’ which collects relevant activity….” The company uses a consumer’s data for targeting that “may be limited to a specific deep action (such as a shopping search, or lead generating auto interaction), while in others, such as age or gender, multiple registration-based data points may be accumulated on the user in the segment”.

  17. 17.

    Turn, “Turn Media Platform Overview,” http://www.turn.com/?p=3055; Turn, “The Ingredients of Our Secret Sauce: Part 1,” http://www.turn.com/?p=5973 (both viewed 15 Feb. 2011).

  18. 18.

    Turn, “Mining Data for Digital Advertising,” http://www.turn.com/?p=4014 (viewed 15 Feb. 2011).

  19. 19.

    Turn, “The Ingredients of Our Secret Sauce: Part 1.”

  20. 20.

    Turn, “Site Privacy Policy,” http://www.turn.com/?page_id=534 (viewed 15 Feb. 2011).

  21. 21.

    Turn, “General Info,” http://www.turn.com/?page_id=532; Turn, “Info Collection & Use,” http://www.turn.com/?page_id=536; Turn, “Site Privacy Policy”; Turn, “Data Partners,” http://www.turn.com/?p=1392 (all viewed 15 Feb. 2011).

  22. 22.

    TARGUSinfo, “About Us: Our Data,” http://www.targusinfo.com/about/data/ (viewed 15 Feb. 2011).

  23. 23.

    TARGUSinfo, “Solutions: On-Demand Scoring: Display Advertising Optimization,” http://www.targusinfo.com/solutions/scoring/optimization/default.aspx (viewed 15 Feb. 2011).

  24. 24.

    TARGUSinfo, “Solutions: On-Demand Scoring: Advertisers,” emphasis in the original, http://www.targusinfo.com/solutions/scoring/optimization/advertisers.aspx (viewed 15 Feb. 2011).

  25. 25.

    “Targeted Marketing Lists,” http://usa.polk.com/Industries/Media/Communicate/TargetMkt/ (viewed 10 Feb. 2011).

  26. 26.

    As mobile marketer Velti noted in a filing for the U.S. Securities and Exchange Commission, according to ABI Research, mobile marketing and advertising spending is expected to increase from $ 1.64 billion in 2007 to nearly $ 29 billion in 2014. Unlike other media platforms, mobile devices cover a very large installed base and enable access to consumers virtually anytime and anywhere, allowing real-time interaction and engagement. By using a mobile device, campaigns can be further targeted to consumers based on interest, demographic profile, and behavioral characteristics, thereby enabling brands, advertising agencies, mobile operators, and media companies to effectively engage consumers in interactive, measurable advertising, and marketing campaigns. Measure the consumer engagement. Unlike other media platforms, the mobile device is used by the consumer more frequently and over longer periods, providing greater opportunities to generate data on where, when, and how a consumer responds to a marketing or advertising message. Brands, advertising agencies, mobile operators and media companies can leverage this data to motivate a specific consumer action (e.g., a product purchase) at critical moments (e.g., when choosing between products) or at a distinct location (e.g., a nearby retailer).

  27. 27.

    As the new collaborative project explains, “Mobile Rich Media ad units are mobile compatible ad units with various measurable, interactive options which drive greater brand engagement and messaging across to end-users compared to basic banner ads…. Optionally, the ad unit can capture information from the end-user to continue engagements at other times or via other media…. [and] can be dynamically composed so the ad content is targeted to the end-user”.

  28. 28.

    Webtrends, “Analytics,” http://www.webtrends.com/Products/Analytics/Facebook.

  29. 29.

    Social media users are also tracked based on data collected on them that measures their “Viralocity,” (viral coefficient), whether they are “social influencers,” “daily active users,” and other social engagement metrics. One technique used by Facebook and its advertisers to elicit data is “incentivizing social action with rewards.” Such techniques can use third parties to install “tracking pixels” on a Facebook page, which “automatically contact and rewards users when pixels are triggered or activity is observed”.

  30. 30.

    Research conducted by the World Privacy Forum on the Network Advertising Initiative (NAI), the US self-regulatory group created in 1999 (and whose members include Google, Microsoft, and other leading players), has documented the limitations of its approach. See also Network Advertising Initiative, “About the NAI,” http://www.networkadvertising.org/about/ (viewed 24 Mar. 2011).

  31. 31.

    See also The Self-Regulatory Program for Online Behavioral Advertising, “Welcome to the Online Home of the Self-Regulatory Program for Online Behavioral Advertising,” http://www.aboutads.info/ (viewed 24 Mar. 2011).

  32. 32.

    “Your Online Choices,” http://www.youronlinechoices.eu/; For a regular report on online ad exchanges in the EU, see ExchangeWire, http://www.exchangewire.com/ (viewed 5 July 2011).

  33. 33.

    “Consumers Find Behavioral Advertising Choices Compelling With TRUSTe TRUSTed Ads Privacy Platform,” Marketwire, 16 Nov. 2010, http://www.marketwire.com/press-release/Consumers-Find-Behavioral-Advertising-Choices-Compelling-With-TRUSTe-TRUSTed-Ads-Privacy-1354242.htm (viewed 16 Feb. 2011).

  34. 34.

    See, for example Kennard (2010).

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Chester, J. (2012). Cookie Wars: How New Data Profiling and Targeting Techniques Threaten Citizens and Consumers in the “Big Data” Era. In: Gutwirth, S., Leenes, R., De Hert, P., Poullet, Y. (eds) European Data Protection: In Good Health?. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2903-2_4

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