New York Privacy Officers Forum. Online Behavioral Advertising: Emerging Legal and Business Issues

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1 2010 New York Privacy Officers Forum Online Behavioral Advertising: Emerging Legal and Business Issues Aaron P. Simpson Partner, Hunton & Williams LLP (212) Peter Weingard SVP, Marketing, Collective (646) November 4, 2010

2 Online Behavioral Advertising Overview What is online behavioral advertising ( OBA )? Targets advertisements to specific segments of consumers by tracking online activity across websites Theoretically, specific individuals cannot be tracked and profiles are not associated with sensitive personal information Different from contextual advertising, which: Analyzes words on web pages being viewed to provide relevant ads No attempt to correlate data to fit consumers into demographic segments 2

3 OBA Debate Spending on OBA has exploded in the past few years Marketers may pay more than twice as much for targeted ads And targeted ads yield a significantly higher ROI But there has been pushback Congressional inquiries and legislation FTC s Self-Regulatory Principles Privacy advocates sounding the alarm 3

4 Timeline of Key Events November 2007: The FTC hosts an Ehavioral Advertising Town Hall December 2007: The FTC released proposed OBA selfregulatory principles 2008 and 2009: Both the House and Senate held hearings on OBA February 2009: The FTC published a revised set of OBA selfregulatory principles July 2009: Marketing industry associations jointly published Self- Regulatory Principles for OBA May 2010: Congressman Rick Boucher develops discussion draft privacy bill July 2010: Congressman Bobby Rush introduces privacy bill known as the BEST PRACTICES Act 4

5 FTC s Self-Regulatory Principles Issued in February 2009 Four Principles: Transparency and consumer control Reasonable security and limited data retention Express consent for material policy changes Express consent for collection of sensitive data The FTC urged industry to develop workable selfregulatory approaches or risk government intervention and legislation The FTC also noted that the line separating PII and non-pii has become increasingly indistinct 5

6 Industry Self-Regulation July 2009: Five industry associations jointly published the Self-Regulatory Principles for Online Behavioral Advertising Intended to: Correspond with the FTC s Guidance, and Address public education and industry accountability issues

7 Industry Self-Regulation (cont d.) These principles include: Education Transparency Consumer Control Data Security Material Change Sensitive Data Accountability In January 2010, the advertising industry introduced an icon to be added to online ads to inform consumers about behavioral advertising practices

8 Boucher Bill Introduced as a discussion draft in May 2010 Inspired in large part by concerns over behavioral advertising Focused on the collection, use and disclosure of covered information Intentionally stays away from using the term personal information Instead uses the term Covered information, which includes: Internet Protocol addresses, and Other unique identifiers tied to a specific individual or a computer, device, or software application Also uses the term Preference Profiles, which include: Lists of information, categories of information, or preferences associated with a specific individual or a computer or device

9 Boucher Bill (cont d.) Broad prohibition on collecting or disclosing covered information about an individual s online activity for any purpose, unless the company: Issues a privacy notice, and Obtains express affirmative consent Pursuant to an exception, such information can be collected, used and disclosed subject to opt-out consent if all of the following occur: Opt-out mechanism is readily available; Covered information is deleted or anonymized within 18 months after it is first collected; A symbol or seal is placed prominently on the website and near any behavioral advertisements; Links to information about the company s practices Allows individuals to review and modify, or completely opt out of having, a preference profile The ad network does not disclose covered information to any other third party without express affirmative consent of the individual

10 BEST PRACTICES Act Introduced in the House by Bobby Rush (D-Ill.) in July 2010 Also inspired in large part by behavioral advertising concerns Also stays away from the term personal information Confirms FTC s position of blurring line between PII and non-pii Covered information defined similarly to include: IP addresses, and Other unique identifiers, where used to collect, store or identify information about a specific individual or to create or maintain a preference profile Preference profile means: A list of preferences, categories of information, or interests: Associated with an individual or with an individual s computer or other device Inferred from the actual behavior of the individual, the actual use of the individual s computer or other device, or information supplied directly by the individual or other use of a computer or other device; and Compiled and maintained for the purpose of marketing or purposes related to marketing, advertising, or sales

11 BEST PRACTICES Act (cont d.) Broad prohibition on monitoring an individual s Internet browsing and collecting, using or disclosing information concerning such activity, except: With the express affirmative consent of the individual; For the purpose of making such information accessible to the individual or for use by the individual; or Pursuant to other exceptions under the Act Must provide individuals with opportunity to: Review and change preference profiles based on a unique persistent identifier Exemption to this requirement for those organizations that join a self-regulatory Choice Program

12 International Issues Companies doing business online also must consider legal issues outside the U.S. The EU Data Protection Directive imposes onerous requirements on the processing of personal data both online and offline IP addresses generally considered personal data Comprehensive data protection laws adopted outside of Europe E.g., in Canada, Argentina, Mexico, Dubai, South Korea Other nations codify privacy in consumer protection laws 12

13 Enforcement Trends FTC will be more proactive going forward Blurring of PI and non-pi will continue Director of Bureau of Consumer Protection plans to step up FTC s law enforcement efforts Focus on data collection practices OBA is under the spotlight Rush bill is gaining traction and features: FTC enforcement State AG enforcement Private right of action 13

14 Looking Ahead Marketing innovations are real and could be extremely beneficial Many exciting technological advances also provoke public anxiety Regulators must address genuine concerns about privacy and data accumulation The evolving legal landscape creates uncertainties for business 14

15 Once upon a time Content was a proxy for an advertiser s audience.

16 Declining reach of television One I Love Lucy = Six CSI s.

17 The Attention Economy As audiences fragment, it becomes impossible for brands to reach specific audiences at scale through any single media.

18 Online audience fragmentation The audience is dispersed over millions of sites and billions of pages. How do you efficiently achieve reach? Top 10 Websites accounted for 70% of all ad revenue in Q (IAB) Unique visitors across the Collective Display, June 9, 2010.

19 Sites vs. Audiences Even within large sites, it can be tough to find your audience. ESPN.com demonstrates how content is a weak proxy for audience. Using the site to reach M would yield a: 40% chance of reaching women. 66% chance of reaching the wrong age and gender. Making a $10 CPM grow to a $30 ecpm to reach your target. Source: Nielsen NetView - ESPN.com June 2010

20 Data: The New Proxy Data allows advertisers to reach specific audiences at scale. Audience-driven buying now accounts for 60% of online display media spending.

21 How does it work? The cookie is a text file with an anonymous ID# Ad systems read the cookie and look in their database for matching attributes. The appropriate ad is served news auto m gourmet

22 Different types of data Implicit Composition Skew Not User-Based Example: Context, Site Explicit User-Based Inferred Topic-modeled Group Skew Example: PRIZM Registered Topic-specific Individual/Household Data Online Offline Online hand-raisers Retargeting Example: Purchasers, Intenders

23 Where does data come from?

24 Data as an analytical tool Data can also surprise us, and force us to rethink our idea of who the right customer or prospect is

25 Benefits of targeting Allows advertisers to reach target audiences at scale. Allows publishers to share in revenue dispersed over a fragmented ecosystem. Provides for more relevant advertising. Helps marketers understand their audience.

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