Suro Senen
Date: May 27, 2026
Source: Partner Insights via Digiday
Subject: The Evolution of Demand-Side Platforms (DSPs) in the Converged TV Era
In the rapidly shifting landscape of modern media, the advertising industry is suffering from a paradox: despite an unprecedented abundance of data signals—ranging from identity graphs to sophisticated contextual intelligence—TV strategies are failing at the point of execution. According to Oscar Rondon, vice president of data and measurement solutions at Nexxen, the industry does not have a data problem; it has an execution problem.
As the lines between linear television and Connected TV (CTV) continue to blur, the industry is reaching a critical inflection point. The winners of the next decade will not be the companies that merely accumulate the most integrations, but those that can synthesize complex viewership data into a singular, actionable strategy.
The Core Problem: Fragmentation and the "Execution Gap"
For years, the promise of programmatic advertising was the ability to reach the right person at the right time with the right message. However, as TV viewing habits have fragmented across streaming platforms, linear broadcast, and on-demand services, the infrastructure used to manage these campaigns has lagged behind.
Currently, many advertisers operate within a fragmented stack. A brand might use one tool for audience planning, another for supply procurement, and a third for post-campaign measurement. This "leaky" ecosystem results in strategy dilution. When data is siloed, insights gained from a campaign often arrive too late to be useful, turning measurement into a post-mortem exercise rather than a live optimization tool.
The crux of the issue is the quality of the signal. While contextual and attention-based data are gaining traction, they are often constrained by small sample sizes or probabilistic assumptions. To achieve true scale and reliability, the industry requires a foundational signal—one that is deterministic, household-level, and cross-platform. That signal is Automatic Content Recognition (ACR) data.
Chronology of the Shift: From Broad Reach to Deterministic Precision
The transition from traditional television buying to the current converged model has been defined by three distinct phases:
- The Linear Era (Pre-2015): Advertising was driven primarily by panel-based estimates. Reach and frequency were broad, and success was measured in GRPs (Gross Rating Points). Data was directional, not deterministic.
- The "Walled Garden" Phase (2015–2022): As CTV emerged, digital-first platforms introduced household-level targeting. However, these platforms operated in silos, making it nearly impossible for advertisers to understand total reach across both linear and streaming channels.
- The Converged Era (2023–Present): We are now in the era of unification. Advertisers are demanding a single view of the consumer. ACR data has emerged as the "connective tissue" of this era, allowing brands to see exactly what was watched, by whom, and how frequently, regardless of the delivery mechanism.
Supporting Data: Why ACR is the Foundational Signal
To understand the necessity of ACR, one must look at the limitations of its peers. Contextual intelligence and attention metrics are valuable, but they serve different functions in the advertising hierarchy.
Contextual Intelligence: The "Where"
Contextual intelligence focuses on the environment—the genre of the show, the mood of the viewer, and the alignment of the creative. It is essential for brand safety and relevance. However, contextual signals cannot, on their own, confirm whether an ad was actually seen or how it contributed to a conversion. It provides the setting for the message but lacks the proof of consumption.
Attention Measurement: The "Quality" Signal
Attention measurement—using computer vision and panel testing—is excellent for assessing the quality of an impression. It answers: "Was the viewer actually looking at the screen?" While this is a high-value data point, it is usually limited by small sample sizes that struggle to scale across the massive, fragmented reach of national TV campaigns.
The ACR Advantage: The "Foundational" Signal
ACR data acts as the ground truth. It provides deterministic insights into what is appearing on the screen. When layered with contextual and attention data, it creates a robust, three-dimensional view of the campaign. ACR tells you who saw it; attention tells you if they were engaged; context tells you where it happened. Without the ACR layer, the other signals lack the scale required for enterprise-level decisioning.
Official Perspective: The DSP as an Operating System
Oscar Rondon of Nexxen emphasizes that the Demand-Side Platform (DSP) must move beyond its traditional role as a mere "bidding engine." If the DSP is truly the control panel of modern advertising, it must be the place where strategy is not just executed, but understood.
"When ACR data, contextual intelligence, supply, and measurement all operate within the same decisioning environment, execution changes," says Rondon.
When these components are unified, the workflow changes from a reactive process to an active one:
- Unified Planning and Activation: By keeping the strategy within the DSP, the campaign remains faithful to the initial intent, avoiding the dilution that occurs when data is passed between disconnected vendors.
- Real-Time Frequency Management: Instead of relying on modeled estimates of how often a household sees an ad, ACR allows for deterministic control, ensuring frequency caps are enforced across both linear and streaming environments.
- The Feedback Loop: Measurement data no longer sits in a static dashboard at the end of a campaign. Instead, it feeds directly back into the DSP, allowing for automated optimizations while the campaign is still in market.
Strategic Implications for Advertisers
For brands, the shift toward a DSP with "native TV intelligence" has profound implications. As TV planning becomes a converged exercise, the ability to manage incremental reach becomes the primary competitive advantage.
1. Eliminating Theoretical Strategy
Many TV strategies fail because they are based on theoretical models of reach. By using native ACR data within a DSP, advertisers can move from "probabilistic reach" to "actual reach." This enables brands to identify exactly when they have reached the point of diminishing returns, allowing them to shift budget to under-penetrated households in real-time.
2. Cross-Screen Cohesion
Modern viewers do not differentiate between "streaming" and "linear"—they simply watch TV. Advertisers who fail to bridge this gap provide a fragmented user experience. A unified DSP ensures that storytelling is consistent across all screens, preventing the frustration of repetitive or disjointed messaging.
3. Outcomes Over Impressions
The era of optimizing for CPMs or simple reach is ending. The focus has shifted to outcomes—whether that is a website visit, a store purchase, or a brand lift survey result. Because a unified DSP links exposure data (ACR) to conversion data, it enables the DSP to act as an "operating system" for business growth, rather than just a tool for buying media inventory.
Conclusion: The Future of the DSP
The next era of television advertising will not be won by the platform with the longest list of third-party integrations, nor by the one with the most complex dashboard. It will be won by the platform that can natively unify viewership data, supply, and measurement into a single, high-speed ecosystem.
As the industry moves toward this model, the DSP will cease to be a "bidding tool" and instead evolve into a comprehensive operating system for the TV business. For advertisers, this means the end of "execution gaps" and the beginning of a future where every dollar spent on TV is backed by deterministic data, real-time intelligence, and measurable business outcomes. In a landscape defined by complexity, the companies that simplify their stack—by placing ACR at the center—will be the ones that turn strategy into lasting market impact.
Azzam Bilal Chamdy
Pevita Pearce
