“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 Carla Holtze, CEO and co-founder at Parrable.
People-based marketing – the ability to reach the right person, at the right time, on the right device – has been a practice that only the walled gardens, such as Facebook, have been able to achieve to date.
Outside of the walled gardens, there has been a collective effort by several companies to stitch together data from different sources to enable people-based marketing. These data graphs being created are a valiant effort to give advertisers the same success in reaching their audiences as they could with Facebook, thus leveling the playing field for the industry.
Several years ago, LiveRamp DLX and Targus built a bridge between the known and unknown worlds. These companies created a privacy-safe mechanism to bring offline data online. While nobody may have used this exact term, what those onboarding companies essentially created was a “cross-channel graph” that enabled the sharing of insights across multiple channels in a privacy-safe way. For example, they could use rich consumer data from CRM files to inform digital media campaigns.
A few years ago, Tapad and other cross-device companies coined the term “cross-device graph” to describe the probabilistic mapping of one or more devices together as belonging to the same user. Probabilistic mapping uses a series of data points – often including IP address, third-party cookies and purchased log file data – to try to triangulate the user’s phone together with their computer, tablet and other devices. Aggregating data via the cross-device graph expanded the way digital advertising was purchased, enabled more effective measurement of how spend in one channel became conversions in another and helped increase the value of inventory.
The creation and use of the various graphs has significantly increased the value of digital advertising over the past five years. Even so, in many instances, probabilistic device mapping is only accurate within a threshold of certainty, limited by visibility in the lack of persistent and overlapping identifiers. More importantly, due to the transient nature of probabilistic mapping forces, one is required to pay repeatedly to re-map the same onboarded data and device links.
There has been a lot of conversation about fixing what’s broken in digital media. Digital media needs a more effective mechanism to manage pseudonymous digital identities – a privacy-safe way to maintain state across multiple digital contexts. We need a way to enhance the persistence of the cross-device and other graphs without the use of personally identifiable information such as email addresses or telephone numbers, as those have tended to augment privacy concerns.
The closest the industry has gotten to the establishment of a third-party addressability graph was the DigiTrust – an effort launched in mid-2014 that was perhaps a bit too early for its time. The DigiTrust was a collaboration across 20 different ad-tech companies that attempted to address challenges around third-party pixel syncing.
The key flaw in the DigiTrust approach is that it required a significant majority of tech vendors to jump in at the same time, which was a huge challenge. The DigiTrust also failed to garner enough interest from the buy side. They’ve got a lot of brain power behind them, so it is likely that DigiTrust 2.0, which re-emerged in March, has addressed these issues.
There are several hurdles that must be overcome for a third-party addressability graph to be successful.
It is impractical to think that all data companies, brands, publishers and ad-tech companies will jump into the pool at the same time to participate in this renewed effort. First, movers will take the lead and the addressability graph will grow incrementally. In order for that to happen, it needs to be backward-compatible with commonly utilized tracking approaches such as cookies, web beacons and mobile advertising identifiers.
The addressability graph providers should not be in the media business or the data space, and they should focus solely on pseudonymous identification. The addressability graph should have an identity currency that is noncompetitive to its clients and thus can be used by everyone as the foundation for their data management efforts.
Any time there’s a new technique in digital advertising, privacy advocates and the Federal Trade Commission have historically stepped in to evaluate. This is true of any of the aforementioned graphs. Similarly, the addressability graph will need the blessing of current industry groups, such as the Network Advertising Initiative and Digital Advertising Alliance. And in the EU, a certification program, such as the EuroPrise, will be helpful in building trust.
It may make sense for advertisers or tech companies to pool their graphs. This is already happening with certain device-graph platforms where a co-op has been set up across multiple advertisers or tech vendors. This approach necessitates some level of cooperation across multiple entities, and it would impact scale while further decreasing page load times by minimizing unnecessary third-party connections.
I believe that the development of the addressability graph will be the next big thing in digital media. And it’s not a matter of if, but when, as we are already hearing about some of the larger marketing cloud platforms attempting to build out their own addressability graphs.
As these products are developed, I hope that these principles are incorporated into the build of the most powerful graph that can be used collectively by the industry to reach and measure the right audiences.