By Stephen Emsall, Strategic Planning Director at MiQ
YouTube is the most prominent video publishing platform across all of in-stream, native, and video formats. Undoubtedly, it’s the most rewarding channel when it comes to unique user reach.
It’s little surprise that the shift in ad spend from offline to digital since the first coronavirus lockdown has seen an increase in video display advertising in the UK by 19% in 2020. But despite this, YouTube is still one of the hardest channels for advertisers to achieve ROI. So why is one of the most popular channels so difficult for advertisers to crack?
YouTube has no customisable insights, and doesn’t offer a deep dive into the infinite number of data touch points. It’s very much an off-the-peg solution and offers no way for advertisers to tailor these insights to their needs. In addition, real-time optimisation is a big challenge. Static post-campaign reports which DV360 provides, prevent brands from utilising campaign insights in real time. And as learning and doing better next time is the essence of good marketing, teams of skilful programmatic traders need to be given the right tools to optimise strategies in-flight.
Although YouTube causes a vast amount of media waste, the audience is likely to engage through the channel. That is why advertisers are reluctant to leave the platform out when building campaigns. If any other platform wasn’t performing, advertisers would likely shift focus to a more profitable touch point. Even though an ‘in it to win it’ mindset has developed among advertisers, there is no assurance they can actually succeed.
However, as with all conundrums, there is a solution. For advertisers, the solution is the YouTube API. While this tool is available and free to use by anyone, a combination of money, expertise and time to efficiently analyse the data is needed to use it right.
Solving the YouTube conundrum
The YouTube API is a great source of data on all the content uploaded to the platform, which marketers can use to gain far deeper insights in a much shorter time. Anyone can plug into the YouTube API and access this data, but it’s unlikely that advertising agencies are tapping into this potential. As the volume of data that can be accessed is so immense, most companies are not equipped with sufficient technological or data science capacity to analyse it in a timely and cost-efficient way.
Another exciting solution for an advertiser is category overlap. By monitoring individual video IDs within categories, it’s easy to determine what types of content resonate well and find closely overlapping groups. Once these categories are connected, it empowers advertisers to make impressive changes to their activation strategy and expand a campaign’s reach to more like-minded audiences.
In addition, multi demand-side platforms (DSPs) can help advertisers unlock the immense potential of first-party data and still be able to tap into YouTube alongside other open web strategies. For instance, taking top-performing videos from a campaign and matching these video descriptions to similar videos on YouTube via the API, can allow to extend the reach of the campaign beyond standard audience targeting.
With that said, having access to granular data on the channels and videos where ads are displaying also helps in reducing waste within relevant categories. Often while companies are displaying ads in particular categories, there might be content that is off the mark and has little in common with the initial target. However, with the capability to monitor individual video IDs, this issue can be easily overcome. In practice, marketers could swiftly exclude anything that’s not relevant to the campaign, minimising unnecessary media wastage. Valuable insights can also empower agencies to make better use of video descriptions and keywords to identify trends in users’ content consumption patterns.
Being able to see the contextual environments the adverts are appearing at a granular level via the API means that suddenly brands are able to minimise their wastage, ensure they are relevant and begin to truly understand what contextual signals help drive performance when advertising on YouTube.
By far, the most exciting opportunity that awaits is connecting YouTube to wider marketing strategies. Depending on the datasets in a market, advertisers can also connect YouTube data to other sources of information such as TV data.
Today, UK-based brands are able to use anonymised mobile data to get a unified view of audiences’ viewing habits across all the screens. Without using a single cookie, agencies can combine consistent YouTube datasets that power omnichannel planning and activation. Gaining and connecting these insights will drive better performance and ensure vital capacity for the cookieless future.