As Google Rolls Out Its Attribution Tool, How Should Publishers Respond?

The Sell Sider” is a column written by the sell side of the digital media community.

Today’s column is written by Tom Noyes, CEO at Commerce Signals.

A popular sports adage is “The best defense is a good offense.” That’s sensible advice for digital publishers in responding to Google Attribution.

Historically, publishers used data on audience traffic, engagement and interests to drive yield and to help sell ads. In response, buyers happily incorporated those measures into their own ad effectiveness programs. Unfortunately, along the way, two serious unintended consequences resulted.

First, measuring on clicks incentivized disreputable sources to monetize bots and nonviewable inventory. Second, these measures also fueled the growth of nontransparent intermediaries that ultimately harmed publisher yields and created buy-side confusion on what ads really cost. In short, we can trace many of the ills in the ad tech ecosystem to how it’s measured.

Now, we have Google Attribution, which measures credit card purchases post-ad impression. This is an important breakthrough: Ad effectiveness now can be determined by whether real people, responsibly deidentified and aggregated, actually buy online or offline. Advertisers can now perform this measurement at scale and cost-effectively.

Measuring post ad-impression purchases begins to address some of those unintended consequences. Most notably, since bots and nonviewable inventory can’t buy anything, disreputable sources get naturally deprioritized. This could significantly reduce the need for separate viewability verification, eliminating both its expense and technology between ad seller and buyer.

Publishers may play defense by seeking to measure credit card purchases post-ad impression, but they can and should instead become two-way players and go on offense by emphasizing real business outcomes through the value of their own content.

The key to becoming a good two-way player requires reimagining the value proposition to ad buyers. That is, publishers ought to transition from selling impressions or actions to guaranteeing real business results for buyers. This implies less defending semi-commoditized CPMs and more ensuring that content really drives revenue for the buyer.

Measurement is often thought of as the buyer’s friend, but in this case, it also offers at least three strategic advantages for two-way playing publishers.

First, the publisher’s narrative and business model are more aligned with the core interest of ad buyers, directly answering the question of whether customers buy advertised products. Traffic, engagement and profiles are interesting enough; however, connecting ad impressions to real revenue for the buyer is a fully aligned discussion.

Second, publishers will develop valuable yield-optimizing insights as they tune results on behalf of the buyer. Even more importantly, knowing what drives value for buyers creates pricing power for publishers. In time, publishers will learn to arbitrage this insight across buyers, creating interesting new business model possibilities.

Third, publishers can leverage their own low incremental costs to deliver outcomes that are of much higher value to ad buyers. Rather than defending the indefensible – premium CPMs in the face of virtually unlimited supply – the publishing narrative focuses on driving and getting paid for meaningful business outcomes for buyers.

It’s time for publishers to go on offense.

Follow Commerce Signals (@CommerceSignals) and AdExchanger (@adexchanger) on Twitter.

1 Comment

  1. Not news. You've been able to measure ad exposure's impact on credit card spend for years with Niesen Buyer Insights. And all of this relies on google serving you an ad that is tied to a household's creditcard spend. Huge reliance on google reliably matching based on an email address, which is one of the lowest %match keys.


Add a comment

XHTML: You can use these tags: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>