This is the first of five Innovator Spotlight articles from our new Special Report, The Contextual Revolution, Five Companies Rewriting The Rules Of CTV Advertising. You can download the report for free thanks to Gracenote and our other sponsors.

“To understand the motivation for Gracenote’s move into contextual advertising, it’s helpful to know our history,” says Trent Wheeler, Head of Product Innovation at Gracenote. “Over time, we’ve built the industry’s broadest, deepest entertainment content dataset. Descriptive Gracenote metadata and content IDs now cover more than 40M titles in 35 languages and 80 countries.” 

ALAN WOLK (AW): Was that the primary driver behind Gracenote’s decision to move into contextual advertising?

TRENT WHEELER (TW): Exactly. For years, these offerings have powered content navigation, search and discovery capabilities, which help video services connect their users to programming. First, this was for linear TV and then evolved into streaming. Now, many of the world’s leading connected TV platforms and entertainment providers also use Gracenote to drive content consumption, user engagement and time spent. 

The industry broadly acknowledges that there’s a big pain point in contextual CTV advertising today: The buy and sell-sides don’t have an agreed-upon language to describe the content that ads appear in. This causes a disconnect. As a result, publishers regularly apply their own naming conventions to content descriptions, which are often unstructured and inconsistent. This basic problem prevents contextual CTV advertising from becoming a scalable solution for marketers and meeting its full potential. 

We knew this was an area where Gracenote’s data expertise could play a huge role. Our descriptive metadata and content IDs, which are already used by the industry, have the ability to address the primary pain point by serving as a common language to facilitate contextual ad selling and buying transactions

AW: How does Gracenote’s long history and expertise in discovery support this shift?

TW: Based on the broad integrations of Gracenote metadata and IDs by top publishers for content discovery use cases, we’re a known entity. Our offerings fuel consumer-facing experiences and help to drive engagement with the content that viewers will enjoy most. For example, when a customer UI presents a collection of programs organized under a label such as “Carefree TV,” Gracenote mood data is the underlying enabler. This helps the publisher attract and retain users, increase loyalty and maximize monetization - today’s top business imperatives.

Practically speaking, the same data being used to categorize and present content choices to viewers can also be used for ad targeting. In fact, our video data and IDs were being passed through in programmatic bidstreams by a number of publishers which was explicit validation of what we knew to be true: Our expansion into contextual advertising would meet a significant need in the marketplace.

AW: How is Gracenote helping advertisers to address the challenges they are finding in regard to audience targeting and content relevance?

TW: To maximize campaign performance, advertisers are really looking to CTV as a way to add incremental reach to what they can get from linear. In addition, when audience based targeting is not possible due to privacy opt-outs, targeting against the content that viewers are interested in and engaging with is an effective solution. 

Contextual targeting in CTV programming enables brands to gain exposure to new consumers by aligning with content that matches their values and voices or otherwise meets specific criteria such as storyline elements, featured talent or even cast inclusivity. 

Further, in open marketplace buys, Gracenote’s contextual metadata and standardized taxonomy helps ensure that publisher inventory doesn’t have metadata gaps that can limit bid matching. Through partner DSPs, we enhance inventory by applying multi-dimensional genres and contextual segments to maximize monetization opportunities. For curated and private marketplace deals, we optimize publishers’ ability to package their inventory by in-depth metadata and contextual segments. 

We can also help target look-alike audiences which provide proxies for traditional demographic based audiences. For example, if a publisher needed to deliver a stand-in for an audience of affluent women, they could segment by top program genres among females such as romance or comedy as well as top moods like thoughtful, powerful or heartwarming to help an advertiser reach these consumers. Our connection to Nielsen gives us the unique ability to use viewing trends to inform our audience segments and base them on the characteristics of programs that attract those audiences. 

AW: You’ve said that Gracenote’s metadata and standardized taxonomy is a big step forward for advertisers. Why is that?

TW: The industry is in general agreement that buyers and sellers need a standard, scaled language to use when describing programming. Contextual advertising in CTV can’t grow without it. Advertisers seeking maximum reach through cross-platform buys are hampered here. Consequently, they have fewer opportunities to engage with likely consumers. Publishers are constrained as well because they’re missing out on monetization opportunities.

Once more descriptive data is available and more contextual signals are flowing through the ecosystem, targeting against appropriate programming will get better. By putting the right ads in front of the right viewers based on the context of the content they’re watching, campaign performance will improve. Better campaign results will bring more ad dollars into CTV, which will further drive the virtuous cycle. This represents a massive step forward for both sides.

AW: How is your solution helping advertisers unlock inventory that might otherwise be overlooked?

TW: The industry is still buying on channel-level data today. Program-level targeting is in the early stages based on a relative dearth of program-level signals and the fact that metadata is not being shared. Our ability to include aggregated data around programs within a channel – but without revealing title-specific information – is a key to unlocking additional ad inventory that has historically been overlooked.

Also, when more content attributes are available in the bidstream, the value of the inventory becomes known, creating more opportunities to match content with suitable bids. To understand the extent to which programmatic bid requests included basic content attributes, we recently conducted an analysis. Looking at more than 20 billion SSP bid requests over one week, we found that only 32% included genre information. Our own data tells us that each piece of CTV content has an average of at least 1.6 genres. But because only one-third of the inventory in this sample had genre information, advertisers had no meaningful visibility into the genres of the majority of content available via programmatic transaction.

There’s a clear opportunity here to facilitate much greater transparency into content inventory. The metadata associated with Gracenote IDs holds the power to increase targetable contextual signals such as genre, rating and program type in order to unlock the value of inventory at scale.

AW: You have partnerships with Peer39 and Magnite. How are those deals working to create new opportunities for advertisers?

TW: Gracenote is providing Peer39 access to our program metadata and IDs for contextual categories that can be targeted within integrated DSPs. This allows advertisers to target and allocate budget to specific Gracenote genres, ratings, program types, parental warnings, as well as Gracenote branded custom contextual categories such as mood, inclusivity, sports enthusiasts and more. In the case of Magnite, one of the industry’s leading SSPs, they’re supporting publishers passing our IDs for open marketplace deals. We’ve done the work to translate these IDs into biddable contextual segments within a number of DSPs today.