Authored by: Sonja Kristiansen, VP Platform Partnerships, TripleLift
The very definition of Native – fully integrated, non-standard ad experiences – is the reason that placements are so varied today. When something is defined as “non-standard,” there is sure to be a wide array of approaches and interpretations of the meaning.
The IAB’s Native 1.2 Spec was introduced in 2017 to provide guardrails and clarity around the identification of Native ad types including In-Feed, In-Article, Peripheral and Recommendation Widget placements. These ad types vary dramatically by aesthetic, user experience, and performance. Few DSPs give advertisers the ability to select between these ad types and as a result, many marketers still aren’t clear on what kind of Native placements they are buying programmatically. Instead, they are beholden to algorithms that determine which Native placement type they end up with.
In comparison, video, another form of advertising with an array of creative experiences, has wide adoption in targeting, transparency and reporting around the different formats available. The idea of having no controls across in-stream, out-stream, CTV or in-banner video buying would be absurd. As a result every leading DSP with video buying capabilities has targeting controls for different placement types, enabling marketers to pick and choose the video inventory that best suits their goals. Although standard for video, most DSPs are still grappling with how to integrate this level of sophistication into their Native inventory targeting.
TripleLift placements are classified by placement type in the bid request, making it possible for DSPs to decision on behalf of advertiser needs. DSPs like DV360 and Zemanta are paving the way by providing their buyers with Native Placement Type targeting capabilities, giving marketers more opportunities to be selective in their Native needs.
With this targeting capability, it is important for advertisers to understand the key differences between Native placement types such as user experience and performance, to make an informed decision.
One major difference in Native ad types is the design of the placement itself, and ultimately the user experience. In-Feed ads are integrated into the stream of content, and often match the look and feel of the publisher environment, while Recommendation Widgets group multiple ads, typically below articles and feeds within fixed placements.
From an advertiser perspective, these are dramatically different ad experiences, yet, they are all defined as “Native”. Advertisers may be surprised to learn that their Native ad is running alongside a group of other ads within a widget, when they intended their ad to live within the stream of content with 100% SOV, like 90% of TripleLift placements.
Aside from user experience, different Native ad types have very different performance benchmarks. In a blind placement type test conducted by TripleLift and a major DSP, In-Article performance was 64% higher than Recommendation widgets, while TripleLift’s In-Article performance was an additional 22% higher than other exchange’s In-Article placements. When considering the visuals above, this may come as no surprise — performance follows user attention, and user attention lives within the stream of content they intend to consume. Considering that most programmatic advertisers optimize towards user attention and performance, the Native placement type marketers choose can make a meaningful difference on campaign success.
As the advent of Native Placement Type Targeting nears, transparency across the entire buying ecosystem will be imperative. We expect to see a wave of adjustments come over the industry as more information around placement type location and performance becomes readily available to help marketers make informed decisions. For DSPs, we anticipate more controls will be added to bring parity to targeting across all formats, including Native.
Reach out to us to learn how you can start targeting quality Native Placement Types today.