How to perfect targeting with contextual YouTube video ads

In an industry where change is the only constant, one strategy has continued to stick around: contextual targeting. Why? Because reaching people during moments of intention can be incredibly powerful. Couple this with ever-evolving industry regulations, and contextual targeting becomes more than just better ROI, but can also make life just a little bit easier for marketers.

This is why I’m so bullish on contextual strategies. Contextual advertising, when executed appropriately, has shown results that can far surpass audience-based buying—and it is ripe for reconsideration. But, of course, it all starts with having the right tools in your marketing toolbox to identify the most effective videos against which to place your ad.

One of the biggest challenges with contextual advertising has always been having enough granular signals to truly identify, understand, and separate appropriate videos from inappropriate ones. Nobody wants their contextual advertising campaigns to appear adjacent to mislabeled segments, misaligned audiences or unsuitable content, which can result in negative ROI, or worse, reputational damage.

The easiest way to solve for this has always been to implement channel or segment-level blocks across content, but blocking entire swaths of supply can have equally adverse effects on your campaigns. Unfortunately, the tools that exist today for marketers to properly manage context can lack certain capabilities to efficiently manage this. For example, how can you use technology to identify inappropriate videos from within a segment or channel and block them while still delivering on desirable content from within that same segment or channel? The answer is control at the individual video level.

Video ID control

Consider a news channel on YouTube. You might not want your ads appearing next to topics such as war, famine, pestilence and death (to name a few). But you also don’t want to block an entire channel because only some of its content might include these topics.

Or say you’re selling sports equipment and want to target popular influencers from the sports and entertainment world, but then a few individual videos from your chosen influencers use overly salty language that violates your brand guidelines. What do you do? Block the channels entirely? If you do that, you lose potentially worthwhile eyeballs and miss out on the other highly desired and brand-safe content on those channels.

We are also all aware of specific creators who are massively popular but sometimes produce objectionable content. The traditional approach to avoiding this content would be to block that entire creator’s channel, but if you can drill down to the specific video ID, you can still run on the suitable and safe videos while eliminating delivery on the rest. The aforementioned “blunt blocking tactics,” which have been logistically necessary for some campaigns, can be overkill.

It’s actually not much different from running a search campaign, where you have the syntax and keywords that make sense for a brand. Just like that, we can slice and dice hundreds of thousands of videos that make sense instead of lumping channels and creators together that may not.

Next-gen contextual intelligence

When we launched GP’s next-gen contextual intelligence platform, we built it with video-ID-level controls, for YouTube, in mind, as opposed to using a more general signal for channel ID. This provides marketers with tools to take a more surgical approach to targeting and blocking strategies. I’m happy to say the results have been encouraging.

We conducted a three-month marketing campaign on YouTube on behalf of a beauty brand partner using our video ID controls and an A/B test against the traditional affinity targeting tools that are available to them. Ads placed precisely against well-identified videos outperformed the traditional affinity methods by three-and-a-half times when measuring user engagement. Further, the average number of pages consumed on the brand’s website was boosted more than 12 times and had a 9% lower bounce rate.

 

GP also delivered a heavy majority of the budget on contextually relevant categories versus when the campaign was targeted to natively available affinity segments.

placement_analysis

 

This A/B test also showed us that without GP’s video ID controls, just 15% of the ads were delivered on aligned content versus when GP’s tools were activated, and our client achieved 95% delivery on aligned (beauty/skincare-related) content. 

aligned_delivery_comparison

 

The primary takeaways are the increased user engagement metrics, as well as the quality/brand-suitability and relevant nature of the videos that the media delivered.

Cutting through the noise

Video-ID-level targeting can also be beneficial on any online video campaign, whether that is YouTube, CTV/OTT and/or within other walled gardens. Our goal has been to streamline the process for marketers, making it easy for them to cut through the noise, target what’s needed and block the rest. All to increase their ability to deliver against tougher and tougher KPIs.

Marketers also care about having contextual targeting solutions entirely independent of cookies (which will likely, maybe, go away … at some point …), and that can avoid tedious and evolving regulations around user targeting. So besides enjoying more impactful and measurable outcomes from your target audience, contextual targeting provides an elegant strategy to protect yourself from not only existing industry challenges, but also future-proofing against anything new that might be introduced around user targeting, privacy or anything else yet to come.

Which we know it will, so better to get ahead of the game now.

Click here to hear about more benefits of contextual targeting at the video ID level.

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