Home Publishers Bloomberg Wants Contextual Targeting To Work In Live Video

Bloomberg Wants Contextual Targeting To Work In Live Video

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Live video is a strong demand driver for streamers and social media. Why not news publishers?

Bloomberg produces hours of live content a day, between its TV channel and its network of global and business news publications. And it’s shifting its contextual targeting focus beyond standard display ads to live video. 

Kym Nicholas, who leads Bloomberg’s global media planning and campaign management (PCM) team, sits at the center of that effort. Her group connects advertisers to Bloomberg’s audience across nine platforms, from TV and digital video to newsletters and branded content.

As Bloomberg rethinks how its live video campaigns are planned and measured, the PCM team is juggling competing demands, Nicholas said. Buyers want cross-platform reach but also granular targeting, accurate measurement and as little exposure to programmatic waste as possible. 

To meet those demands, Bloomberg is rolling out new audience tools, video targeting capabilities and a revamped revenue operations structure that treats planning, ad ops and client services as a single “client success” function.

Real-time contextual targeting for video

Like most publishers, Bloomberg often talks about “starting with the brief,” Nicholas said. 

The PCM team operationalizes campaign briefs across Bloomberg’s properties, including the Bloomberg Television, News and Businessweek divisions. It follows campaigns through delivery, reporting and optimization, partnering with sales and client marketing to shape the response and staying attached as the campaign runs.

Given this hands-on service, the PCM team works almost exclusively on direct IO and programmatic guaranteed deals, not open programmatic.

To track audience behavior across its properties, Bloomberg uses a proprietary audience and content platform called Bloomberg AiQ, launched in 2017. The solution analyzes content and format preferences to suggest newsletter sponsorships, editorial franchises or video series that align with a given brief.

“It’s a really great way for us to pinpoint specific contextual alignment opportunities or specific newsletter or video sponsorships,” Nicholas said.

Historically, Bloomberg saved its contextual precision mostly for display campaigns. Its approach to video, especially live video, was more suited for broad reach than surgical alignment.

But Bloomberg introduced another tool, called AdService, in 2025 to bring contextual intelligence to its video content. It analyzes data points such as video descriptions and closed captions, looking for keywords and themes in near real time, then uses that signal to dynamically match ads to content.

The latest development is extending AdService’s capabilities across Bloomberg’s near-24/7 live video output, Nicholas said. 

Still, AdService’s contextual targeting is only an option for video campaigns, not the default. Bloomberg is conscious of not “targeting for targeting’s sake,” Nicholas said. If the core audience is already a good fit for an advertiser’s brief, the PCM team may deliberately keep targeting broader audiences to maximize reach. 

But when the brief calls for specificity – such as targeting a particular subset of business decision-makers – the PCM team leans harder on contextual adjacencies and first-party audience targeting.

The underlying sales pitch is that Bloomberg can deliver high-volume, high-quality impressions and dial targeting up or down depending on the objective. 

Measurement, reporting and the role of AI

If the front end of Bloomberg’s story is about audience tools and contextual video, the back end is about how to measure all of it without drowning in operational work.

Buyers increasingly expect near real-time reporting and transparent measurement frameworks, especially as AI becomes table stakes in marketing stacks. Bloomberg already has “an enormous amount of data” on how its platforms perform and which audiences are best reached where, Nicholas said. The harder part is stitching those data sources together quickly and consistently across a wide array of formats and a mix of brand and performance objectives. That’s where AI tools are starting to play a role.

“We do a good job of bringing it all together [ourselves],” she said. But, regarding the growing demand from buyers for more AI-based measurement, she added, “it’s just a case of wanting to do that more quickly and less manually, and being less reliant on our data science and insights team.”

For now, Bloomberg’s AI experiments are focused on improving workflows, not on replacing planners. PCM is testing AI features inside internal tools and collaboration platforms to surface relevant information faster. For example, the team is using these tools to quickly find editorial franchises that fit a brief or for surfacing new contextual opportunities that planners might otherwise miss.

Using AI, Bloomberg’s long-term ambition is to reduce manual reporting and move toward real-time dashboards spanning all nine of its platforms, Nicholas said. 

However, each new AI-enabled reporting capability has to fit within Bloomberg’s existing structure in which PCM, ad ops and client services already work as a unified front, Nicholas added. The technology is there to make their jobs easier, not to blow up the process.

“We have big ambitions,” she said of AI and cross-platform reporting. “But it’s one step at a time in terms of how we roll them out.”

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