Google and Apple ID Data Changes Compel Brands to Reach Consciousness Stage Four

Google and Apple are putting up barriers to the deterministic matching of data the industry has gotten accustomed to using. Indeed, these steps follow world lawmaking shifts to greater privacy protection, and world advertiser shifts to avoiding excessive use of retargeting as discussed in my previous column. How they affect a brand depends upon the brand's stage in the evolution of its advertising value consciousness, as explained below, because the times demand a clear understanding of why the brand ought to use a particular key performance indicator (KPI) versus another, and the KPI chosen has an impact on the degree to which one benefits from deterministic match data at scale.

What are the stages of brand consciousness? Let's begin with an analogy. Scientists speak of there being three stages of civilization:

  1. Those which have not achieved space travel: Stage One Civilizations
  2. Those which have space travel within their own solar systems: Stage Two Civilizations
  3. Those which have attained space travel among the stars: Stage Three Civilizations

In marketing, the understanding of how to value specific advertising campaigns has not evolved very far. But there have been huge leaps. Twenty years ago, the global advertising industry generally believed that advertising sales effects could not be measured outside of direct marketing. Today there is widespread use of Marketing Mix Modeling (MMM), Multitouch Attribution (MTA), Singlesource, National Time Series, Matched Market Trials and Random Control Trials (RCTs), primarily addressing sales effects or proxies for same. Alongside those there are brand lift and tracking studies which focus on upper funnel branding metrics. All of these present differing (yet sometimes consilient) evaluations of an advertising campaign that has run or is still running.

Some of these ad evaluation methods are more dependent than others upon the ability to deterministically match IDs.For example, MMM, National Time Series and Matched Market Trials are not dependent upon the ability to match IDs deterministically, whereas MTA, Singlesource and RCTs in general are highly dependent upon such matching. These therefore will be the techniques that are most deprecated by the reduction in ID matchability.

Experts whom I trust are estimating that for those who have been using masses of digital inventory, match rates will probably decrease to about a third of what they are now.

This will lower the accuracy of the ROI measurement methods that are dependent upon ID matching, except in the cases where publishers have strong ID data that will still be usable by marketers. This latter advantage will greatly benefit MVPDs, AVODs, Digital Print (Meredith, Hearst, et al), Smart TV manufacturers and purveyors of connective devices (Roku, Amazon, et al), especially as advertisers and agencies make their cautious shifts to these platforms from today's dominant digital platforms specifically because of ID matchability.

Within advertiser organizations there are four Stages of understanding of how to evaluate the effectiveness of advertising:

Let's say that you are an eCom/DTC. The value to you of retargeting and being able to track a specific household over time is very high; it's basic to your business. You need high match rate deterministic targeting and will be among the first to shift from today's dominant platforms to those which retain these core capabilities. The more you can get households to reveal their identity to you in order to invite a closer relationship the better. Dealing with cohorts or aggregates of any kind is not going to do you a lot of good.

The higher up you are in the Stages the more obvious this will be to you. It will not be hard to convince others in your organization and you can take advantage of Google and Apple publicity right now to state your case to engage inventory suppliers that preserve your right to "market with a memory">

Bill Harvey

Bill Harvey, who won an Emmy® Award in 2022 for his invention of set top box data, has spent over 35 years leading the way in media research with pioneer thinking in New Media, set top box data, optimizers, measurement standards, privacy standards, the A… read more