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The latest edition of the IAS Media Quality report for H2 2017 featured U.S. media quality benchmarks broken down by type of buy. By comparing publisher direct to programmatic benchmarks, we are able to extrapolate unique insights which can be attributed to each buy type. This allows us to isolate insights that are unique to programmatic buys. For example, we’ve seen significant improvement in programmatic viewability especially in video across global markets that has outpaced increases in overall viewability.
During our webinar for the H2 2017 Media Quality Report, Transparency in Digital, we received many questions around our programmatic media quality benchmarks. We tapped into our proprietary data and consulted our team of programmatic experts to provide the answers below.
Q: How do fraud detection strategies differ between programmatic and publisher direct buy types?
Programmatic buying offers advertisers opportunities for efficiency and scale that didn’t previously exist in digital advertising. With advances in machine learning and automation, marketers can clean inventory in real time instead of relying on post-bid reporting and manual optimization.
However, for all of its efficiency, programmatic does present advertisers with some unique challenges. In a direct buy, advertisers have considerably more control over where their ads appear. Programmatic buyers surrenders some of this control in exchange for scale which increases the risk of fraud. Direct buyers can utilize monitoring and blocking technology to detect fraud, block impressions on sites with high fraud levels, and request make goods on lost inventory.
In programmatic, these methods of fraud mitigation are less applicable. Advertisers dont have as much control over which publishers are included in their buys. However, there are solutions to strategically mitigate fraud in programmatic opportunities. It’s essential to understand the fraud levels within DSP partners. Through monitoring, advertisers can identify fraud levels that raise concern and work with their DSPs to reduce them.
Q: Beyond monitoring, how can brands proactively reduce their levels of programmatic of fraud?
Pre-bid optimization solutions empower advertisers to avoid bidding on fraudulent impressions before the ad even serves. Through dynamic modeling, optimization partners can identify fraudulent impressions and then prevent the bid from being generated. This solution not only helps the individual advertiser, it helps the ecosystem by stopping impressions from being delivered to fraudsters and thereby reducing the overall incentive to commit fraud for revenue. Most importantly, it saves advertisers money. Programmatic pre-bid optimization solutions offer advertisers a unique opportunity to improve media quality as it relates to fraud, create efficiencies, and save budget without going through the effort to reach out to publishers directly.
Q: Regarding programmatic brand risk, how can marketers protect their brand?
Brand risk has been a growing concern for advertisers. Much of this increased awareness has been driven by media coverage around brands who have found their advertising placed alongside solicitous, inappropriate, or violent content.
Programmatic advertisers share these concerns. Programmatic solutions offer advertisers buying efficiency, data, and scale; however, they also make it more challenging for marketers to establish in which content their advertising lands. The good news is there are actions brands can take to protect themselves and be more confident in the safety of their programmatic strategies.
Brands need to establish their own appetite for risk. For example, advertising on a news article on violent topic may be acceptable for some brands, but would not align with others’ objectives. Because of differing brand safety objectives, each advertiser needs to establish their own risk thresholds and partner with pre-bid solution providers that are able to execute on them. Similar to pre-bid fraud solutions, brands can prevent their ads from being delivered to risky content before the impression is bid upon.
Q: Can advertisers protect themselves against the specific categories of risk for which you provided benchmarks?
Marketers can identify which categories of risk are most important to them. While alcohol-related content may be perfectly acceptable for certain brands, it may present a significant brand risk for another. Once the risk levels and categories have been defined, a brand can work with their programmatic media quality partner to optimize against distributing advertising alongside content that fails to meet their risk thresholds and categories.
Q: Does programmatic brand safety optimization kill scale?
For brands concerned about the loss of scale through programmatic brand safety optimization, there is a strategy that can offer protection without significantly impacting scale. Brands can leverage a pre-bid strategy that addresses moderate and/or high areas of risk. For risk that falls outside of those categories, the best solution is to use blocking post bid.
For additional protection, marketers can layer on a blocking solution that prevents impressions from serving after the bid has been placed. This helps in situations where there are specific low-risk environments a marketer would like to avoid. In this case, excluding higher and moderate risk categories from a pre-bid perspective and then having a specific blocking strategy post bid offers strategic protection without significantly reducing their scale.
Have more questions? Check our our other H2 2017 Media Quality Report Q&A’s below:
