Today's Lift Letter is brought to you by Sonja Kristiansen
The definition of native advertising is a controversial one. Depending on who you ask, you might hear terms like in-feed ads, component-based advertising or even branded content. The very value proposition of native - fully integrated, non-standard ad experiences - is the reason that the definition is so varied today. When something is defined as “non-standard”, there is sure to be a wide array of approaches.
Today, the IAB Native Advertising Playbook recognizes six categories of native ads: In-Feed, Paid Search, Recommendation Widgets, Promoted Listings, In-Ad and Custom. These ad types vary dramatically by aesthetic, user experience, and performance. While it benefits advertisers to have the luxury of choice when it comes to their native advertising needs, it’s somewhat problematic that today, most DSPs don’t differentiate between these ad types. As a result, advertisers buying native advertising programmatically are subject to the algorithm of their bidder to determine which native experience they end up with -- and how they ultimately reach the consumer. For the most part, advertisers are unable to discern between native ad types today when activating programmatically in the open exchange.
In comparison, let’s look at video: another form of advertising with a wide array of creative experiences, from instream, to outstream, to in-banner video. The idea of having no targeting controls across these ad types would be absurd, as the value of premium instream inventory is very different than in-banner video. As such, every leading DSP with video buying capabilities has targeting controls for different placement types, enabling buyers to pick and choose the video inventory that best suits their goals. This is table stakes for video, but since native is still in its teething stage, DSPs have not integrated this level of sophistication -- instead bucketing all native inventory types as “Native”.
There are a few reasons that this matters. For starters, one major difference in native ad types is the design of the placement itself, and ultimately the user experience. The three most common native ad types available programmatically - In-Feed, Recommendation Widget, and In-Ad (or In-Banner Native) are demonstrated below:
In-Feed ads are integrated into the stream of content, and often match the look and feel of the publisher environment (in the case of TripleLift, right down to stylistic elements like fonts, image aspect ratios, colors, etc.), while Recommendation Widgets are a templated format with multiple images and headlines, typically placed below articles. In-Banner ads, on the other hand, occupy standard IAB placements that would typically show a banner ad, but include native components like a headline and caption, allowing them to qualify under the “component-based advertising” definition of native.
From an advertiser perspective, these are dramatically different ad experiences to be defined under a single “native” umbrella. Advertisers and agencies are often surprised to learn that In-Banner Native exists (and may even comprise a significant portion of their budget) as many omni-channel exchanges have recently jumped into native by enabling standard banner placements to render native “components”.
Performance by Ad Type
Aside from user experience, different native ad types have very different performance benchmarks. Per the recent eMarketer Native Digital Display forecast, in-feed ads had the highest clickthrough rate among the native formats studied. Recommendation widgets were clicked on just 40% as frequently, and in-ad native (i.e., IAB standard units with native components inside) got only 13% the CTR of in-feed. 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 can make a meaningful difference on campaign success.
What Happens Next?
With the release of OpenRTB Native Version 1.2, openRTB protocol now allows for these placements to be called out differently in the bid request, allowing advertisers to pick and choose what best suits their definition of native. For the first time ever, DSPs can build support to objectively understand what they’re buying based on signals passed from the exchange, thus providing better targeting controls to advertisers.
Starting last month, all TripleLift placements are now classified by placement type in the bid request, making it possible for DSPs to decision on behalf of advertisers. While some DSPs are building support for this, it won’t make it onto every platform’s roadmap in the near term. While the industry waits for DSPs to adopt support for more native targeting controls, advertisers can rely on exchange targeting as a proxy for selecting the inventory that suits their definition of “native”. In summary, it’s important for advertisers to understand what native placement types are out there, and which exchanges offer which types, to make informed activation decisions that will impact overall performance.