“If you think about the evolution of TV advertising, a lot of what you were buying in the early days of TV was the show. You were aligning your brand to specific pieces of content, and the transparency around that was critical. This really took off with upfront buying, where brands were focused on running in specific shows” notes Amit Nigam, VP, Product at Beachfront. “As streaming TV has grown in the programmatic space, advertisers have readily taken advantage of the audience-centric buying options that exist, but contextual is equally as critical and should not be overlooked.”

ALAN WOLK  (AW): So looking at where the industry is now, why is video-level contextual data becoming so important on CTV?

AMIT NIGAM  (AN):  Video-level contextual data has always been important in CTV and video advertising. Lately, we’ve seen a renaissance around understanding the context of the show that ads are running in.  Moving that understanding into programmatic buying models is important for the continued adoption of CTV as an advertising medium. This is because advertisers know the impact of being aligned with specific content, and how it can help grow their brands. 

Video-level contextual data has always been critical. As a result, you'll continue to see brands lean in and want more of it in programmatic CTV as the space continues to evolve. 

AW: How much pushback are you getting from brands who want greater transparency of programmatic buys?

AN: We see quite a bit of demand for greater contextual transparency in CTV among our advertising partners, and it’s an area we’re really focused on as a business. It is a challenge because, on the one hand, you have buyers who really desire and crave that level of contextual understanding. And then, on the other side, you have publishers who are slightly more reluctant to share contextual information programmatically. If you start to share show-level information as publisher, does that – for example - cannibalize your direct-sold business? Publishers are keen on understanding how sharing those signals impacts the dynamic of their monetization stack, and ultimately want it to be additive to their yield strategies. 

AW: How much does a fear of “cherry picking” factor in, that publishers might be able to sell some parts of their inventory and not others, and that this could negate the benefits of programmatic?

AN:   If you have buyers who are really dialed into show-level information, it can complicate how publishers manage their yield across the programmatic stack. There's a concern that buyers might pull back from their upfront or direct-sold buys because they can access that same specific content programmatically. This is a challenge. Publishers' content is their asset, and they have a right to preserve its value. At the same time, buyers should be able to understand contextually where their ads are going

AW: How is Beachfront working to help brands get a better understanding of context? 

AN: For us, it really starts by working closely with our publisher partners to understand and empower their monetization strategies. As one example, we support and standardize key contextual signals they pass in the bidstream, so that our advertising partners can understand the types of content they are bidding against. 

We also recently introduced a new self-serve deal ID curation platform, Beachfront Select, that brings these signals to the forefront, so that – when provided by publishers – brands can build media plans aligned to specific types of programming. 

And lastly, we also support additional third-party solutions like the IRIS_ID, which helps buyers activate standardized contextual data across supply sources and target specific types of content at a much deeper level. 

We’re ultimately trying to enable as much flexibility, transparency, and control as possible for brands, while ensuring maximum yield for publishers. 

AW:  Can you tell me more about the IRIS_ID? What does it do, and how does it function?

AN: IRIS.TV has effectively made it possible to classify video content beyond the standard IAB genre definitions, enabling a more detailed categorization enriched with AI. The IRIS_ID is the signal that allows AI-powered solutions and currencies to access publishers’ video-level source content data to analyze and create segments. It allows for a deeper understanding of content for more precise contextual targeting as well as planning and measurement. While the IAB has made strides in standardization, IRIS.TV allows publishers to use AI to apply the IAB taxonomy in a consistent and standardized way at scale. This unlocks even more detailed insights into the content's specifics through contextual intelligence that includes custom segments like emotion, celebrities, and logo recognition.

AW: How are you helping publishers and advertisers to capitalize on the value of the IRIS_ID and other content identifiers?

AN: For us, it's about ensuring the inclusion of value-generating, readable signals in the bid stream. Publishers often hesitate to invest in any kind of technology unless they see a clear value. We work closely with our publishers to help them capitalize on contextual opportunities, especially in areas we observe rising CPMs due to the inclusion of specific signals. 

Essentially, we act as a conduit, transmitting the information. If the original request doesn't contain a specific signal, then we can’t pass it as a value. Our role is to help partners understand the value and opportunities associated with  these contextual macros. Additionally, we assist the demand side in accessing more normalized (or readable) signals. This allows them to be more refined in who they're targeting, and also where they are running – balancing precision with campaign scale.

AW: So, you suggest publishers achieve higher CPMs when incorporating more contextual data?

AN: Yes. While it's not a direct guarantee, we generally observe higher CPMs when contextual data is included. A stronger data stream directed at buyers often stimulates better competition, leading to increased bid density and higher CPMs in the bids. This creates a positive feedback loop. 

AW: So, in simpler terms, when there's contextual data attached to a show, more advertisers are interested in bidding for it because they recognize its value?

AN: Exactly. This is a case where knowledge empowers buyers, which in turn increases value for the publishers. That said, CTV also presents a unique challenge compared to online video or desktop. Marking up specific contextual signals is easier for predetermined content than for live-streamed content. That’s why I think we will soon see more focus on CTV in this context. 

The CTV advertising industry initially focused heavily on targeting specific audiences. It’s digital after all. Now, there's a realization that contextual alignment is equally as crucial. Combining both audience and contextual creates a powerful synergy, and I'm optimistic about the industry's direction in this regard.

Beachfront is a founding member of the Alliance for Video-level Contextual Advertising (AVCA), an organization dedicated to funding research into applications of AI for contextual advertising in streaming. Download the AVCA’s recently published consumer research ‘Driving Viewer Attention and Brand Metrics in CTV Advertising: Understanding the Impact of AI in Contextual Targeting.’