“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Lauren Moores, vice president of analytics at EveryScreen Media, a Media6Degrees company.
Ah, the cookie. It’s the mainstay of targeted advertising and the hot button of the privacy debate.
Third-party cookies have long served as the basis of desktop advertising, providing a way for advertisers to retarget users across several sites, generate algorithmic targeting based on browsing behavior, set frequency caps and attribute user engagement. Privacy advocates have often railed against the cookie as an invasive behavioral-tracking tool, but it has remained the chief mechanism for serving relevant advertising across the web.
My colleague Alec Greenberg recently wrote a blog post in defense of the third-party cookie for desktop advertising. I fully support his arguments — when it comes to desktop. But for mobile advertising, the cookie crumbles.
Mobile is fast becoming just as vital to digital advertising success as the desktop, but the mobile environment is infinitely more fragmented, with dozens of device types running on different operating systems and multiple browsers with different rules. The preeminence of apps and the market share of the iPhone and its cookie-free Safari browser make cookies nearly irrelevant in mobile, rendering efforts to track across devices, networks and media immensely difficult.
Multiple technologies have emerged as alternatives to cookies in mobile media. The iOS unique identifier was the first attempt at replacing the mobile cookie. The UDID is associated with a user’s hardware, which allows for mobile ad targeting and attribution across mobile applications and mobile Web for any iOS (Apple) device. However, the UDID raised privacy concerns based on the fact that, unlike cookies, users cannot opt out of this identification and Apple has withdrawn its support for it. The UDID gave way to the MAC address, which essentially had the same drawbacks as the UDID and was also abandoned by most due to privacy concerns.
Static device fingerprints are similar to persistent identifiers, which comprise the user’s device type, location, time, carrier, OS and other attributes. The use of fingerprinting allows advertisers to support mobile campaign measurement per device, across mobile Web and applications. However, privacy is yet again a concern with static digital fingerprints, as they too are immune from opt out. Dynamic digital fingerprinting, where the fingerprint is temporal, can address privacy concerns, but does not allow for cross-device and cross-channel measurement. In addition, the digital fingerprint is unique to the provider who creates it and not a universal identifier.
The Next Era Of Device IDs
The latest evolution of device IDs that attempt to provide an industrywide identifier while addressing privacy issues are dynamic device identifiers, such as the idFA (Apple’s ID For Advertising), which can actually be altered by the consumer. The idFA allows users to opt out of behavioral advertising and enables do-not-track. It is one of the better solutions available to the mobile advertising community, as it can be used across mobile networks and exchanges and allows for measurement across apps and mobile Web. The main drawback to dynamic device IDs is the inability to support cross-device and cross-channel advertising performance attribution.
There are a few industry players working to address the attribution problem by creating an advertiser-agnostic central clearinghouse, where consumers opt in to a universal ID that can be used for targeted advertising and to measure engagement. This approach suffers from a heavy reliance on consumer and market education, and perhaps unrealistic expectations for consumer adoption and industry standardization.
Until then, we have to go back to our roots in science and math and to refocus on users rather than devices to overcome the limitations of cookies in mobile. Applying statistical probabilities to user behaviors online enables advertisers to estimate the likelihood that a user of one device is the same user of any other device, including tablets, smartphones, digital TV, desktop or any other digital device.
This statistical modeling goes well beyond your 11th-grade math class. These powerful technologies can parse billions of data points to determine probabilities and enable advertisers to reach out to users accordingly. These science-based solutions go beyond desktop cookie capabilities — and are inherently respectful of user privacy — by providing a means to identify advertising audiences across channels, resulting in an understanding of overall consumer engagement across brands.
As the media environment continues to fragment, we can’t rest on legacy methods and tools. A better approach is to apply tried-and-true reasoning based on mathematical and scientific principles to address evolving media forms.
On the desktop, the cookie remains the most effective way to serve relevant ads. But as mobile continues to take more share of media consumption, it is vital that we think beyond the cookie to find and engage consumers, no matter where they are or what device they use.
Follow Lauren Moores (@lolomoo) and AdExchanger (@adexchanger) on Twitter.
