Solving for Challenges in CTV Ad Serving – Part 4

In a Q&A that appeared in ExchangeWire, Unruly’s Erhard Neumann, Managing Director of our Spearad ad serving and unified auction platform, discussed the current state of CTV and how TV broadcasters and CTV/OTT content providers can address industry challenges. We’ve divided the interview into quick-hit reads to keep you in the know…fast.

PART 4: Creating Customizable Ad Break Experiences

How should brands direct their creatives to engage CTV audiences? How can they work with publishers and technology partners to ensure their content is customisable and optimised according to specific audiences?

Pricing is not the only rule deciding this, it could also be that some types of ads, especially targeted ads, find a better position at the beginning or end of a break. It’s a combination of determining the business objective of the ad break, and a mix of rules for things like price, competitive separation, ad slot position and targeting the content owner.

Traditional TV relies on panels to identify audience reach throughout the day, while in the CTV and AVOD, similar to digital, ads are served to relevant viewers as they engage with content.

When a user is watching a movie via AVOD for example, there’s a one-to-one connection in which the user is much more sensitive to how many ads are streamed within the AVOD content, the length of the ad, and the relevance. With this one-to-one connection, publishers can be more customised with the ad content and flexible when it comes to the length of ad breaks, to avoid annoying the viewer. If you don’t have enough ads available, just make the ad break shorter – Unruly’s ad server can do that!

To optimise the ad experience, it may also be better to show two ads from the same advertiser but in a way that doesn’t feel like it’s duplicated. You start a story with one ad, and you end it with a second, and in doing so, you tell a story.

Finally, we have a big problem again with the identification of users. You can use meta information that often comes with the content, such as genre, actor, products and language, in combination with data available from households. The same is when you can identify contextual parts of the content and translate them into keys and values, making ad selection for an ad server much more precise than just “targeting a user.” It’s a mix between targeting the user, using meta and contextual information from the content, to deliver the right ads.