“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 Tim Gough, vice president of media solutions at dunnhumby.
As the IAB announced $11.6 billion in online advertising spending for the first quarter alone this year, the inevitable question arose: How is that working out for advertisers?
There are many factors in deciding whether Internet advertising works. With more marketing dollars funneling into digital advertising, we are absolutely right to question the extent to which it does. We have all of the data we need to quantify that, yet we still leave ourselves open to headlines such as “A Dangerous Question: Does Internet Advertising Work at All?”
What’s going wrong? Are we failing to measure digital advertising correctly, or are we not executing it correctly?
Unfortunately, the answer is both. But there is light at the end of the tunnel.
Poor Execution
“Bring on ad blockers,” said David Droga in Cannes recently.
ClarityRay pegs ad-blocking rates as high as 18% for Chrome and Firefox, with some tech sites north of 50%. While it’s true that this proliferation of ad blocking should inspire advertisers to do better, the growth and scale of the technology is a damning indictment of an industry regarded as invasive and, far too often, an irrelevant annoyance.
Instead, taking these users out has the effect of increasing relative response metrics for the rest of ads served, making it appear that ads are getting more engaging when in fact the opposite may be true. So we may continue to see more invasive and annoying ads for that very reason, especially if click rates remain the primary metric of success.
So how do we make effective digital ads which, rather than being intrusive, are welcomed and accepted by users?
The No. 1 factor is creative. Ads must win our attention while still allowing for a seamless experience. But for advertising to be truly effective, it needs to make our online experiences better, as crazy as that sounds. To do that requires the right combination of personalization and relevance, fueled by data-driven targeting.
There is a growing buzz around demand moments as an opportunity for targeted mobile advertising, or essentially targeting consumers when they are most responsive to messaging. Using real-time data to respond to a consumer’s location, needs, intentions and even their mood presents a huge opportunity for marketers, not just in mobile but in all digital advertising.
Targeting ads when a gamer completes a level or when someone is standing on a car lot are simple examples that can be extended far beyond such specific use cases. While demand moments are very much reactive, the longer-term goal is to achieve true personalization and relevance, taking into account my longer-term habits and behaviors, both on and offline.
Online data has long been used in this way, but integrating our offline lives has been a much tougher task. We are now at the point where consumer packaged goods (CPG) companies can achieve previously unavailable targeting precision by serving ads using actual in-store purchasing data to define targeting criteria. This completely changes the dynamics of digital media buying, shifting the focus onto audience quality, which ultimately leads to better performance, rather than simply reach and frequency at a much less granular level.
This additional data also creates more responsibility for the advertiser and must be used with care. Used without context or emotion, our attempts to personalize may actually come across as creepy, and without a customer-first mindset, personalization may not be relevant.
Relevancy is king. When offline data is used with the consumer front-of-mind, the experience and performance is better for all.
The future is bright. While we originally created a market for personalized digital ads, which actually make the Internet seem more cluttered, slow and potentially creepy, we are now moving toward a much more relevant, responsive and seamless future that connects our behavior on and offline to our experiences across all devices.
Taking Stock
Although it is difficult for paid search, we have learned ways to remove the “I-was-gonna-buy-it-anyway” effect for ads served across the open web, mobile and Facebook in order to quantify true incremental uplift.
Exposed consumers can be compared directly to unexposed equivalents who look and behave the same both online and, if appropriate, in-store. The sales uplift, which is then calculated, controls for sales that would have happened anyway and results in a true incremental ROI for the campaign.
But while we are able to successfully define ROI for campaigns executed across a single platform, the greater challenge going forward is to understand the impact of each platform and combination of platforms on purchasing using comparable ROI metrics. Cross-platform measurement and attribution are the next big hurdles and justify some notable recent acquisitions. With so much fragmentation, however, there are still too many platforms and not enough linkages between them all.
From a measurement perspective, panel-based solutions no longer suffice. Only large-scale single-source transactional datasets allow for sales uplift analysis that extends across multiple platforms and devices with the required granularity.
In the near future, CPGs will be able to use the same purchase-based criteria to target consumers across multiple digital channels as part of an integrated campaign. Using single-source measurement, they will be able to understand how each platform interacts with others, and plan and execute future campaigns optimally across platforms, measuring and allocating the correct impact to each platform using attribution.
Ultimately all advertising needs the right measurement metrics and methodology to prove that it is driving incremental sales. The success metric must always be sales.
Going forward, the industry needs to figure out how to deliver engaging yet seamless content across all devices in a way that enhances a consumer’s online and mobile experiences, rather than distracts from them in order for that measurement to demonstrate the scale of impact that is possible.
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