Industry Insights: How audience data is redefining TV advertising performance

Data is no longer a supporting layer in TV advertising, it is becoming the operating system.

Part two of this Industry Insights roundtable examines how broadcasters are using data, analytics and automation to sharpen ad targeting, improve campaign performance and redefine how inventory is valued.

The discussion explores the growing importance of first-party data, the shift toward outcome-based measurement and the role of AI in real-time optimization across linear and streaming environments. As traditional audience proxies give way to richer viewer signals, broadcasters are aligning closer to digital advertising norms while navigating privacy, fragmentation and scale.

This installment focuses on how insight-driven decision-making is reshaping ad sales strategies and setting new expectations for accountability and performance across every screen. 

Key takeaways from this Industry Insights roundtable

• First-party data leads: Broadcasters are prioritizing their own behavioral and contextual data as third-party signals decline.
• Measurement drives value: Inventory pricing increasingly reflects outcomes, engagement and attribution rather than reach alone.
• AI enables optimization: Machine learning is moving campaign management from reactive reporting to real-time decisioning.
• Context matters more: Creative relevance improves as targeting incorporates content signals, mood and viewing behavior.
• Cross-platform alignment grows: Unified data frameworks allow campaigns to optimize consistently across linear, CTV and FAST.

How are broadcasters leveraging data and analytics to enhance ad targeting and campaign performance?

Dave Dembowski, CRO, Operative: With streaming, broadcasters can learn more about audiences and provide elements of digital on the big screen. They can segment and target specific audiences, and serve targeted messaging and content to them. Broadcasters can also leverage a greater variety of performance metrics than on linear, which helps with optimization and improvement over time.

Mrugesh Desai, VP, North America, Accedo: Ad tech has advanced significantly over the last few years, as video service providers have sought to tackle churn by offering ad-based tiers alongside traditional subscription-based packages. Another key driver of ad tech innovation is the rapid advancement of AI which is enabling data to be analyzed much more effectively so that ads can be better targeted allowing personalized ads to be delivered to individual users. This not only helps to ensure a better user experience for the viewer, but also increases ad engagement and conversion rates, which in turn makes ad space much more valuable.

James Varndell, senior director of product management, playback, Bitmovin: For ads to be effective in terms of advertiser ROI, they need to be relevant and interesting to the viewer. This is made possible by the use of data that has enabled ad targeting to improve significantly over the years yet concerns around data privacy and the backlash against the use of third-party cookies is leading broadcasters and video providers to rethink how they use data. First-party data has unsurprisingly become much more valuable, and broadcasters are increasingly using this data alongside other methods such as contextual advertising to enhance ad targeting. 

Mathias Guille, VP, cloud platform, Broadpeak: Broadcasters are blending social, demographic, behavioral and contextual metadata to provide more relevant and up to date audience targeting. Third-party customer data platforms (CDPs), cross-correlation tools and advanced segmentation are also helping provide deeper insight and granularity. Collaborating with distributors — operators and broadband service providers — who offer rich first-party data is also a powerful route to unlocking more accurate campaign optimization.

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Hadar Tel Mizrahi, senior product manager, targeted ads and recommendations, Viaccess-Orca: Broadcasters can segment audiences using a mix of first-party, contextual, and third-party data collected under privacy regulations, enabling more accurate targeting and better ad ROI for advertisers. Analytics platforms identify which segments deliver the strongest results and help allocate impressions more effectively. These platforms also track delivery and guide adjustments to pacing, rotation, and format to improve campaign performance.

Jean Macher, senior director, global SaaS solutions, Harmonic: CTV promises to unify the broad reach of TV ad campaigns with the precision and measurability of digital. While audience-based targeting across multiple CTV publishers remains challenging due to fragmented data sets, advancements in contextual targeting are fueling a new wave of innovation. By analyzing contextual details, such as the “mood” of the video scene, broadcasters can now deliver ads that feel more relevant, natural and effective — enhancing both audience engagement and ad campaign performance.

Jason Fairchild, co-founder and CEO, tvScientific: Data and analytics have become the common language between broadcasters and advertisers. By connecting ad exposures to business outcomes, broadcasters are moving beyond proxy metrics like GRPs and impressions to true performance indicators. This shift accelerates the convergence of TV and digital, turning data into the bridge that enables transparency, accountability, and smarter monetization strategies.

Evan Rutchik, president & chief strategy officer, Viamedia AI: The most meaningful shift is that data is no longer just used to report what happened; it is being used to decide what should happen next. Broadcasters and MVPDs are combining first-party subscriber data with privacy-safe tools like Geo-Graph and LFID to build local audience segments that can be activated across linear and CTV with consistent definitions. As a result, we can adjust schedules mid-flight by shifting dayparts, creative rotations, or allocation between screens based on how specific audiences are actually responding.

Steve Reynolds, CEO, Imagine Communications: Broadcasters are moving from anonymous audiences to rich, trackable viewer profiles. Modern platforms pull in first- and third-party data, device and location signals, and content metadata, then feed it into decision engines that apply broadcast-grade rules at the household level, within the privacy constraints of the region they operate in. With that unified data backbone, broadcasters can measure and optimize across linear, CTV, and FAST with real precision — letting advertisers pay for outcomes and helping broadcasters maximize yield and CPMs.

James Shears, SVP, advertising, ThinkAnalytics: Broadcasters are increasingly realizing that the most meaningful gains come from better activation of their own viewership and content data. Instead of relying solely on third-party datasets, first-party behavioral signals are now acting as an increasingly growing strategic asset, using these signals to understand evolving audience interests, household dynamics, and cross-platform consumption patterns. This shift allows broadcasters to refine ad targeting, improve measurement, and create more monetizable advertising opportunities.

How are first-party data strategies evolving?

Daniel Weinbaum, partner, Altman Solon: Over the past five to seven years, many broadcasters have enhanced their first-party data capabilities to include a broader capture and use of content-based and contextual data from their digital platforms. This enables them to create richer subscriber and household-level profiles. The next critical step is monetizing this enhanced first-party data into revenue opportunities, specifically through addressable advertising, content sales, and audience development use cases. We have seen broadcasters significantly strengthen their data strategies by leveraging clean rooms and forming more selective third-party partnerships. Some have gone further and developed enviable audience graphs that capture broad parts of hard-to-measure consumer segments at a national scale.

Justin Rosen, SVP, data and insights, Ampersand: The smartest advertisers know that those who are able to rely on deterministic, high-quality data will be the most effective at achieving their desired business outcome with every investment they make across every screen. As AI and machine learning become more central to campaign planning and activation, harnessing first-party data exclusively is becoming perhaps the most critical competitive advantage. Industry leaders are focusing not just on scale, but on the quality, transparency, and cross-screen applicability of their data to optimize performance and measurement. The adoption of clean room technology has been an accelerant of this.

James Shears, SVP, advertising, ThinkAnalytics: First-party data strategies are evolving from simple identity resolution to deeper behavioral and contextual intelligence. Broadcasters are beginning to treat their viewership data as a strategic resource for advertising across Linear, VOD and FAST channels—continuously transforming consumption patterns into actionable insights across targeting and content curation. At the same time, AI-driven metadata enrichment is turning content libraries into more dynamic assets, enabling new forms of privacy-safe contextual and behavioral advertising.

Laura Brandano-Lauta,VP, market retail, large agency and inside sales, Comcast Advertising: We see the market looking to inform buying decisions and report on outcomes by leveraging not only the media first-party data, but also advertiser first-party data. And more specifically for outcomes, being able to match back advertiser sales data to their advertising buys shows true ROAS and is a game changer for their business. In fact, when advertisers do not have clean access to their own first party sources, we can unlock major business value by enabling seamless behind the scenes ROAS measurement with partners like MasterCard — it’s as simple as matching ad exposure to transaction data, and the advertiser doesn’t have to lift a finger.

How do changes in measurement and attribution affect how networks value and package inventory?

Dave Dembowski, CRO, Operative: Streaming allows advertisers and media companies to measure more than ever before. This affects how networks price and value different inventory, and helps them serve advertisers who want more targeted, selective media buying. With good measurement, broadcasters can price and package more confidently to get the most value from their products, while delivering on advertisers evolving campaign goals.

Mrugesh Desai, VP, North America, Accedo: Viewers today are actively engaged, and expect flexibility, personalization, and relevance in how content and ads are delivered. As viewers have gravitated away from traditional TV to digital platforms, and increasingly to ad-supported services, this has prompted broadcasters to rethink how they package, price, and deliver ads. Advancements in ad tech are enabling broadcasters to target ads much more precisely so that they closely align with viewers interests and preference.

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Tim Sewell, CEO, Yospace: Accurate measurement can be challenging with DAI at scale across a fragmented landscape of devices and platforms, but it is incredibly important as it’s the single most important metric to advertisers, and the one by which they pay broadcasters. However, broadcasters must manage inconsistent behavior across CTVs, mobile apps, web players, and set-top boxes, as well as differences between streaming protocols HLS and MPEG-DASH. These inconsistencies create gaps in reporting and uncertainty in revenue recognition.

Mathias Guille, VP, cloud platform, Broadpeak: More granular attribution — including spot-level engagement, conversion tracking and cross-device behavior — is reshaping how inventory is priced and sold. Ad value increasingly reflects not just reach, but performance and viewer interaction. This shift is promising, but it demands much better standardization and collaboration across the ad tech stack to ensure transparency and compatibility.

Jason Fairchild, co-founder and CEO, tvScientific: Measurement is finally catching up to the way people watch TV. As attribution becomes deterministic, tying ad exposure directly to outcomes, networks can move beyond traditional CPM pricing toward value-based models. This evolution rewards quality content, transparent reporting, and platforms that can prove performance across every campaign.

Steve Reynolds, CEO, Imagine Communications: They are pushing networks to move from spot-based metrics to audience-based, cross-platform impressions and outcomes, which means inventory now has to be packaged around audience value, not just time slots. As attribution gets more granular across linear, OTT, FAST, and connected environments, networks are pricing inventory based on audience quality, engagement, device reach, and clean deduped counts. The result is a clear premium for high-confidence placements and a steady rise in CPMs for segments that can prove real performance.

Laura Brandano-Lauta,VP, market retail, large agency and inside sales, Comcast Advertising: The main goal for any advertiser is to have a positive net gain to their bottom line resulting from their advertising.  When media companies are able to package inventory based on the audience that an advertiser is trying to target and then is able to prove the results of targeting and reaching that audience, both the media vendor and advertiser win.  Now more than ever, advertisers are laser-focused on measuring impact and how they can optimize results going forward.

How are broadcasters leveraging AI and machine learning to optimize ad placement and predict campaign performance in real time?

Dave Dembowski, CRO, Operative: Broadcasters are taking a page from digital advertising, using AI and machine learning to adjust campaign placement and delivery based on performance in real time. With dynamic ad serving, broadcasters can improve campaign outcomes and help advertisers reach audiences more effectively.

James Varndell, senior director of product management, playback, Bitmovin: For ads to be effective, they obviously need to resonate with the viewer, which means they need to align closely with a viewer’s interests and preferences. Another important factor is the timing of the ad, because ads are also more effective if they’re served to the viewer at the point when the viewer is likely to be the most receptive. With AI-based predictive analytic tools, broadcasters and service providers predict user engagement and conversion rates at different points of the video.

Hadar Tel Mizrahi, senior product manager, targeted ads and recommendations, Viaccess-Orca: Broadcasters use AI and ML to analyze viewing patterns and predict where ads are most likely to be watched rather than skipped. Real-time models adjust pacing, sequencing and placement during the campaign itself, using fresh data to improve ROI as conditions change. AI-driven measurement also forecasts performance and guides ongoing optimization to boost overall campaign efficiency.

Jean Macher, senior director, global SaaS solutions, Harmonic: Broadcasters are increasingly harnessing AI and machine learning to make ad placement more intelligent and adaptive, particularly for in-stream advertising. By analyzing live video streams in real time, AI can identify key moments — such as high- and low-action moments in sports — to trigger contextually relevant, split-screen or overlay ads without disrupting the viewer experience. These data-driven insights also help broadcasters predict campaign performance, optimize monetization opportunities and maintain the perfect balance between engagement and revenue.

Jason Fairchild, co-founder and CEO, tvScientific: AI is transforming TV advertising from reactive to predictive. Machine learning enables real-time decisioning, optimizing ad placement, creative rotation, and audience selection to maximize performance. By combining automation with human-led strategy, broadcasters can deliver ads with greater precision, efficiency, and impact at scale.

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Evan Rutchik, president & chief strategy officer, Viamedia AI: AI’s real value is in automating the repetitive decisions humans have historically had to make manually, i.e. what placement to prioritize, how to shift budget, when to cap frequency for a certain audience. Our machine learning models analyze delivery patterns and engagement by segment and continuously re-weight the mix of linear versus CTV, or one inventory source versus another, to stay on pace with campaign goals. That doesn’t replace human judgment, but it gives planners and operators a more accurate, real-time picture of where each additional dollar should go.

Steve Reynolds, CEO, Imagine Communications: Broadcasters are turning to AI and machine learning instead of relying solely on historical logs and manual adjustments. These tools analyze viewership patterns and audience targets on the fly, automatically shifting placements to improve yield and reduce waste. They also automate schedule changes — bumping lower-value spots for higher-value orders when needed — which cuts down on manual work and makes the whole operation far more responsive to campaign demands.

How are broadcasters approaching creative versioning and dynamic creative optimization to personalize viewer experiences?

Dave Dembowski, CRO, Operative: While still an evolving part of content distribution enabled via the digital capabilities of streaming, broadcasters are increasingly using creative versioning and dynamic creative optimization (DCO) to tailor content and advertising to individual viewer preferences in real time. By leveraging audience data and AI-driven insights, they can adjust visuals, messaging, and formats based on demographics, behaviors, or viewing context. This personalized approach enhances engagement, improves ad effectiveness, and strengthens viewer loyalty.

Roger Franklin, chief strategy officer, LTN: Broadcasters can leverage graphic overlays and different audio tracks that help advertisers move viewers along a marketing journey without having to shoot and produce a large number of different, but similar, video ad segments. These elements can also be tailored to personalize the message whenever a specific viewer is known to be watching a program.

Daniel Weinbaum, partner, Altman Solon: Advances in dynamic creative optimization (DCO) and generative AI-led creative technology allow broadcasters to offer access to quality creative development at a lower cost. This helps them reach SMB and mid-market advertisers with smaller budgets. Additionally, broadcasters are increasingly making their valuable first-party audience, content, and contextual-related data available to their in-house agencies and third-party partners to assist advertisers in developing creative for more targeted, cross-channel and cross-format usage.

Hadar Tel Mizrahi, senior product manager, targeted ads and recommendations, Viaccess-Orca: Dynamic creative optimization personalizes creative elements, such as images, text, and calls to action, based on user context. This boosts relevance and engagement. Generative AI accelerates creative variation and enables automated versioning at scale. Industry signals, mainly Netflix’s statements about 2026, suggest that once creative variation matures, ad formats themselves will be the next layer to undergo personalization.