If an ad is served but no one views it, does it have the opportunity to make an impact?
Digital advertising used to be simple. Back in the days when websites were cleaner, with a very limited number of ad formats running on desktop computers, as an industry, we felt reasonably comfortable that an ad served equated to an ad viewed. Operating within the most measurable advertising medium, digital analytics professionals led the way in establishing standards and methodologies by which digital campaign success was evaluated. Consumers who were served an ad had an “opportunity to see” the ad. Those who were walking in the footprint of the same campaign, but were not served the ad did not. By comparing outcome metrics between the two groups (e.g.,brand attitudes and online conversions, later offline sales), we were able to quantify whether the digital campaign contributed to an incremental lift in success, proving Return on Ad Spend (ROAS). We also used these results to optimize campaigns, leveraging the key drivers of campaign effectiveness, such as ad frequency, different creative executions and media placements.
We now live in a world propelled by technological advances, where consumers often quickly scroll past the ads in their haste to get to other engaging content. This means that ads often remain hidden from consumers view, sitting in a different frame or tab. To add to viewability challenges, fraud runs rampant within the $327 billion global digital ad industry.
According to the IAS Media Quality benchmarks, an average display media campaign is susceptible to 25% ad fraud when not optimized to prevent it. Furthermore, over 37% of impressions go unseen by the campaign audience. This means that as many as 53% of ads served (taking into account fraud and viewability duplication) are never seen by real humans. Linking ads to the consumers they were served to, IAS internal data shows that roughly 35% of a display campaign audience never see a viewable ad. Yet, the ability to measure digital ad effectiveness and return on ad spend, largely hasn’t evolved to account for these market complexities.
Ad verification is foundational to campaign success
Ad verification metrics are predominantly used to monitor and optimize towards viewable and fraud-free impressions, served in a brand-safe environment. Together as an industry, we have made significant strides in improving the quality of ad impressions that are bought and sold . As John Montgomery, EVP Global Brand Safety at GroupM recently articulated in an interview with Beet.TV, “So we know that we are getting viewable ads that are viewed by a human in the right demographic in a contextually-safe environment, we’re saying what does that mean (and we’re calling that “quality”)? What does that mean for effectiveness?”
Improving ad verification measurement and optimization is an ongoing initiative that is essential to ensuring that digital campaigns have a strong foundation for success. Technological innovation and consumer behavior will continue to dictate which new devices and platforms need to be monitored and managed for viewability and brand safety. And as long as the digital ad industry remains lucrative, fraudsters will not stop developing new ways to game the system.
What we believe John’s quote represents is a shift in the way marketers view ad verification in campaign planning and execution. Now with more confidence that real consumers have the opportunity to see digital ads in a brand-safe environment, the focus can shift to whether and how those “quality” impressions contributed to campaign effectiveness.
Ad verification metrics drive campaign effectiveness
Optimizing for verification metrics helps improve consumers’ “opportunity to see” the campaign creative. But does that guarantee those impressions had an “opportunity to influence” consumers towards outcomes that advertising was intended to achieve?
To address this key performance question, IAS developed Online Conversion Lift to:
- Ensure that campaign effectiveness is measured by true consumer exposure; and
- Leverage this methodology to understand how exposure time influences campaign success.
Advertising is intended to influence consumers. We need to evolve from traditional ad effectiveness practice of defining campaign exposure by ads served, to one that determines exposure by a human audience that had the opportunity to see the ads. Verification metrics enable accurate measurement by allowing us to remove fraudulent ads, and ensuring only consumers who were exposed to ads that met industry guidelines of viewability are considered “exposed” to the campaign.
On the other hand, consumers who were served non-viewable ads provide a sample universe for a comparison group. IAS samples a control group of consumers, who share the same characteristics as those who were actually exposed to the campaign. We then quantify campaign impact by measuring the difference in conversion between those exposed to the campaign and those who weren’t. This method is cost effective as we utilize impressions that were already purchased but not viewed.
The ability to distinguish between the value an ad delivers when it is viewed for 1-2 seconds (per industry guidelines) versus when it is viewed for 30-40 seconds (for example), is essential to understand how to maximize the impact of a campaign. If industry viewability guidelines dictate the minimum time at which consumers have an ‘opportunity to see’ an ad, the time beyond that represents the ad’s ‘opportunity to influence’ consumers. Our R&D effort shows that within the opportunity to influence window there is typically an optimal exposure time when consumers are most likely to engage in actions that drive campaign KPIs. Achieving or optimizing for that time-in-view is important to ensure the campaign is set up to deliver maximum impact.
Online Conversion Lift from IAS leverages ad verification metrics to accurately measure digital campaign effectiveness in order to help advertisers plan effective, outcome-driven digital campaigns. Our granular reporting enables advertisers to optimize their campaigns based on time-in-view and frequency data across media partners and placements to minimize waste and maximize impact. To learn more, check out the one sheet.
