Last week we heard the big news that Twitter launched a new advertising network known as the “Twitter Audience Platform” which offers additional ad options to marketers and increased reach beyond the Twitter platform itself.
Over the past few years we’ve undoubtedly seen an abundant rise of new media channels popping up in rapid succession, along with an explosion of mobile devices that are transforming consumer buying behaviors. However, with new channels and devices come new challenges for us marketers on how to measure marketing interactions.
Seeing the sea change in the market, the folks at eMarketer created the report, “Cross-Platform Attribution: Device Identification, Big Data Pose Continued Challenges”, to clarify what’s currently happening in cross-platform attribution and highlight the complications marketers face in achieving a truly complete view. Featured in the report is OptiMine’s own chief marketing officer, Matt Voda, along with other top industry leaders.
This past week, Verizon reached an agreement to buy AOL for $4.4 billion. Yes, $4.4 billion. As shock hit the web, many pondered why Verizon would buy into the once thriving internet company? Initial reports linking the acquisition to content (AOL currently owns The Huffington Post and TechCrunch) weren't quite on target.
SO WHY PAY BILLIONS OF DOLLARS FOR THAT?
As it turns out, it was all about the ad tech. As the digital advertising industry moves toward automation, for the past few years AOL has been acquiring companies that help in every step of the ad buying and measurement processes. As the ad industry is forced to evolve to the massive mobile tidal wave and the surge in programmatic buying, it is clear that traditional forms of ad tech – tracking, measurement and optimization – no longer apply. With the acquisition of AOL and its ad tech platforms, and Verizon’s access to millions of consumers and their behavioral data, the company clearly wants to be in the epicenter of this new ecosystem.
We’ve been watching cookies crumble for some time now, with major browsers moving to block cookies and the increasingly widespread understanding of cookies’ multi-faceted limitations – chief among them the inability to track users across devices in today’s multi-device world. Facebook’s Atlas launch is just further, resounding testament to the inevitability of cookies’ demise (and the shakiness of attribution solutions which rely on them as their foundation). As head of Atlas Erik Johnson noted:“Cookies don’t work on mobile, are becoming less accurate in demographic targeting and can’t easily or accurately measure the customer purchase funnel across browsers and devices or into the offline world.”
While aspects of Facebook’s Atlas indeed may offer reasons for advertisers to applaud, in other areas it does little to overcome cookies’ limitations – and, in fact, introduces new complications for marketers. Read on to understand what’s good, bad and (still) ugly about this latest move to replace cookies.
The findings explored in this eMarketer article concern me. That brands are increasingly using social media to reach their audience is great news, but the lack of understanding of the true value of the audience is troubling. Counting the number of “Likes”, “clickthroughs”, and “Retweets” is a reasonable exercise and it does have value, but it cannot take the place of measuring the effectiveness of social content using financial metrics.
And that is where my concern comes in.
The world of digital advertising is filled with shiny objects and one of the shiniest is mobile. According to an article published in VenturBeat, Juniper predicts that in-app advertising will reach $17 billion by 2018. That’s an increase of almost 400% over the meager $3.5 billion spent in 2013.
Taken in isolation, the rapid rise of spending on in-app ads is quite a story. But when placed side-by-side with this recent report from eMarketer, advertisers have a new variable to consider before spending their next in-app ad dollar.
Editor's Note: The following is the second in a series of interviews with OptiMine CTO Rob Cooley on the subject of measuring the cross-channel value of digital advertising. In the first installment, which can be found here, Rob talked about the importance of measuring cross-channel value and different approaches to solving the problem. In part II, he discusses the obstacles that lay in the way of achieving the goal: measuring how much a particular ad affects the financial performance of another ad.
When we last sat down, we talked about the effect upper funnel ad impressions have on the conversion performance of lower funnel ads such as search and retargeting. What I’d like to talk about today is the obstacles that lie in the path to measuring cross-ad / or cross-channel value.
Q: If we think about upper funnel impressions and their effect on search alone, measuring the impact of every single ad on every single keyword, easily leads to millions of individual measurement events for an advertiser.
Yes. Let’s say you have a thousand upper funnel ads and you’re trying to measure the impact of those ads on a thousand keywords, you have one million relationships to analyze. What we find the reality to be though, is that they have as many as fifty upper funnel ads. So it isn’t going to be a thousand times a thousand, rather it tends to be fifty times ten thousand or a hundred thousand or more, so you can easily get to a million.
Note: For the purposes of this post, the terms cross-platform and cross-channel are used interchangeably.
Welcome to the third installment of our series where we break down the eMarketer report “Cross-Platform Attribution: A Status Report on Overcoming Select Attribution Challenges.” If you haven’t read part I or II, or if you’d like to refresh your memory, you will find them here and here.
Last time out we focused on two types of attribution—bottom-up and top-down—and the role each one plays. In this case, value measurement and spend allocation respectively. We also inferred, unequivocally declared really, that attribution, regardless of the type, will never solve the problems it sets out to solve. There are several reasons for this and we are going to explore two in this post; viewability and third-party cookies. In part IV of our series we’ll dive deeper into the current rage of all digital advertising channels and one heck of an obstacle in its own right, mobile.