Without a doubt, Connected TV (CTV) is the most exciting new frontier for digital advertising. As more people snip the cord on traditional cable and move towards streaming giants like Netflix and Hulu, advertisers are following their eyeballs. For brands, success on CTV is a top priority to maximize ROI, increase brand awareness and reach audiences. And as modern ad tech tries to catch up, we are just beginning to explore the true potential and scale of this media opportunity.
In this blog post, we will explore why marketers & publishers should go beyond rudimentary CTV signals and lean into video-level data and universal content identifiers as they ramp up their CTV marketing this year and beyond.
What are the challenges of targeting your audience on CTV?
Yes, developing CTV-focused marketing plans is all well and good until you come to the questions of: who is the person behind the screen? How do I reach my user? The audience addressability we’ve taken for granted on the open web is not directly transferable to CTV and with increasing privacy regulations, this will get much harder over time.
The basis of CTV targeting is currently generic demographic, topic and geographic data that is not campaign- or brand-specific, and we don’t always know who is sitting in the living room behind the screen. So, in a marketplace where audience reach, relevance and addressability are so important, how can we target in a more granular, audience-specific way on CTV?
How can you tactically target your CTV audience in today’s world?
While other ad platforms are playing catch up, AI-driven advanced contextual technology is now available on scalable platforms to help you reach your audiences in the right moments, within the right content, across CTV.
Advanced contextual technology is a cutting-edge approach that leverages sophisticated algorithms and data analytics to deliver highly targeted and relevant ads to CTV viewers. This technology ensures that ads are seen at the most opportune moments, maximizing engagement and conversion rates. As CTV continues to grow in popularity, advanced contextual technology promises to reshape the landscape of our industry by offering unprecedented levels of targeting and effectiveness. But, there are still some challenges in transacting on video-level data at scale.
How does it work?
In order to reap the benefits of advanced contextual technology, advertisers must rely on tech providers to analyze contextual cues within the content being streamed, by analyzing content at the video level. Due to ecosystem limitations, it can be challenging to gain access to video files themselves in the bidstream, unlike url page data.
The promise of scalability for transactable video-level data across CTV lies in the adoption of universal content ID providers, such as IRIS.TV’s IRIS_ID. Leading content data platforms like IRIS.TV work directly with publishers to assign a unique identifier to a given video asset which can be passed through the bidstream, enabling contextual targeting at the video level.
What is video-level contextual targeting via a content ID?
While most contextual providers just analyze the genre, name or app description to categorize content, GumGum VerityTM has the capability to analyze CTV content at the video level and make these signals available to advertisers for targeting in major DSPs through its partnership with IRIS.TV.
This means that Verity™ can look at every component of the video, from the metadata to the audio transcription, to the text and imagery, making sure that whichever ad is placed within the video is impactful and resonates with the right audiences. Advertisers can leverage this video-level targeting methodology in their DSPs via the IRIS_ID, IRIS.TV’s unique identifier that makes it possible to transact on these signals within the programmatic ecosystem.
As viewers are watching content across hundreds of apps and streaming services in a fragmented CTV landscape, Such precision makes sure that ads are placed in relevant and brand suitable environments and that good quality content is not unnecessarily blocked. For example, there may be highly relevant Olympic content on a CTV news app. Without the content ID and video-level analysis, though, there’s no way to know that the inventory is relevant; the CTV app title & description will likely only reveal that the inventory is related to news content, not sports. As a result, valuable video inventory is blocked and advertisers miss out on key and premium sports content that could be great for ads.
When a video has an IRIS_ID, it includes all segments Verity™ has created for that video. This solves for fragmentation as it allows advertisers to target what viewers are watching regardless of what device, app, or channel the program appears on. For example, if we want to target “Anime” content, it’s unrealistic to go to every single app and have them each curate anime content for us. IRIS.TV provides advertisers with a centralized solution across all apps.
Can I buy video-level CTV today, and is it scalable?
As of June 1, 2024, GumGum Verity™ expanded its partnership with IRIS.TV to incorporate universal content ID-driven CTV targeting in major DSPs to allow for granular video-level targeting with improved capabilities. Many top tier CTV publishers have begun adopting the IRIS_ID content signal in order to make their inventory available for contextual targeting in the DSP; however, we still have a long way to go to achieve a full ecosystem adoption of this single currency.
Don’t miss out on great advertising moments—activate video-level analysis on your chosen DSPs, and speak to your CTV supply partners about adopting universal content ID signals, like the IRIS_ID, to ensure you can target at the video-level at scale.
How can you activate it?
You can now apply accredited data from Verity™ to your programmatic CTV campaigns for video-level targeting leveraging the IRIS_ID via contextual targeting segments in major DSPs, extending your rich media strategy and supply sources.
It is simple and easy to activate:
