‘Interest-Based’ Online Targeting of Pharmaceutical Advertising

In interest-based targeting, or behavioral targeting (BT), users’ online behavior (specifically what content they visit) drives the advertising profile that determines future advertising delivery. So, if a user visits a jewelry site—say, shopping for an engagement ring— they start seeing jewelry ads popping up all over. This seems innocuous enough, until your girlfriend uses your lap top and sees advertising for Blue Nile, an online jeweler, everywhere she goes. This happened to me recently and is a great example of BT gone awry.

BT’s proponents argue that more relevant advertising creates a win-win-win relationship for all parties: The consumer will value the advertising more. The advertiser delivers a more targeted message to a more likely prospect. The publisher gets more revenue from advertisers who get better results.

BEWARE THE ‘ICK’ FACTOR

Opponents of BT argue that the process— gathering behind-the-scenes surfing history and sharing it with data exchanges, ad networks and other BT ecosystems— is too opaque. A user should be able to expect some privacy while surfing. The simplest criticism one can relate to (especially after being “followed” from site to site by the same ad) is, “It’s creepy”. Critics press for disclosure (transparency) and control (allowing consumers to opt-out). These issues echo the much larger questions about privacy expectations on the web.

Our already heavily regulated industry faces particular challenges when it comes to interest-based targeting. If we can identify a potential sufferer of a condition, put the power and strength of pharmaceutical marketing resources to work, and help more patients to seek and receive therapy— that is a significant win-win-win.

But what about user privacy? While BT certainly seems harmless for some conditions (such as allergies or GERD) or for some audiences (like physicians and healthcare professionals who expect to be marketed to in all manners), pharmaceutical DTC advertising with BT raises some serious concerns. Most of us would agree that it is not appropriate for antiretroviral ads to “follow” a user who is researching HIV symptoms. What about breast cancer? What could happen with this data if it was linked to an individual and fell into the hands of managed care? Could it be used to deny insurance coverage? So many issues arise when collecting healthcare data, even if it is supposed to remain anonymous.

SELF-REGULATION

The advertising industry has created guidelines for BT—the “Self-Regulatory Principles for Online Behavioral Advertising,” assembled and endorsed by the Digital Advertising Alliance (DAA). This consortium of industry trade groups includes: the American Association of Advertising Agencies, the American Advertising Federation, the Association of National Advertisers, the Council of Better Business Bureaus, the Direct Marketing Association, the Interactive Advertising Bureau and the Network Advertising Initiative. These guidelines outline seven major principles that those who employ BT should follow, specifically: Educating consumers, providing transparency, providing consumer control (and the ability to opt-out), securing the data, gaining consumer consent for material changes to policies and collection methods, a sensitive data principle, and an accountability principle.

The Federal Trade Commission and Congress are watching behavioral targeting closely. Many in Washington feel that the industry has not gone far enough to police itself. In 2010, the FTC proposed a legislative framework for U.S. consumer data privacy that included a “Do Not Track” mechanism. And 2011 saw the introduction of numerous other bills, with names like the Do Not Track Me Online Act of 2011 and the Kerry /McCain Commercial Privacy Bill of Rights Act of 2011, both of which appoint FTC as the rule maker and enforcer of online behavioral targeting.

Here’s my advice to the pharmaceutical industry. Work with credible, trustworthy partners. And segregate your data collection and targeting efforts into “risk” categories, then experiment in the lower risk category while avoiding higher risks. BT works, and works well, but does expose your brand and company to new risks. Understand what your partners do with data today and how they use it tomorrow (ignorance is no excuse). Finally, make sure the return on investment justifies any increased risk.

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