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PUBLISHER: IDC | PRODUCT CODE: 1940183

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PUBLISHER: IDC | PRODUCT CODE: 1940183

Tackling CTV Advertising Identity, Measurement, and Frequency in a Closed-Loop Ecosystem for Campaign Optimization

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PAGES: 18 Pages
DELIVERY TIME: 1-2 business days
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This IDC Perspective explores the transformation of connected TV (CTV) advertising into a closed-loop, performance-driven ecosystem, as showcased at CES 2026. Industry leaders have operationalized identity interoperability, real-time measurement, and frequency governance through authenticated identity graphs, privacy-safe clean rooms, and AI-powered optimization. Key partnerships such as Amazon DSP and Roku demonstrate deterministic reach and outcome-based attribution, while retail media networks (RMNs) inject commerce intent and purchase data to enhance targeting and campaign efficiency. The result is a unified framework where ad exposure is directly linked to business outcomes, enabling advertisers to optimize for ROAS, conversion lift, and frequency efficiency. The document concludes with actionable guidance for stakeholders to invest in interoperable identity solutions, shift KPIs to outcome metrics, and leverage closed-loop feedback for rapid campaign improvement."In the new era of CTV, the real breakthrough isn't more screens, it's the seamless fusion of authenticated identity, privacy-safe data collaboration, and real-time outcome optimization," stated Alex Holtz, research director, Worldwide Media and Entertainment Digital Strategies at IDC. "The winners will be those who can connect every impression to a measurable result, transforming CTV from a reach-driven channel into a closed-loop engine for accountable performance. The question is no longer who can deliver ads, but who can prove they drive business outcomes at scale."

Product Code: US54230426

Executive snapshot

  • Key takeaways
  • Recommended actions

Situation overview

  • Advertising framework for CTV ecosystem
  • Closed-loop workflows and ecosystem collaboration
    • Identity and audience data enrichment
      • Audience insights and segmentation
      • Closed-loop measurement and ROAS optimization
      • Impact on CTR and ROAS
        • How RMNs improve frequency control
        • How RMNs improve CTR and support real-time bidding
      • CTV + RMN closed-loop playbook explained
      • RMNs enable closed-loop attribution
      • Sample use cases
        • Data flow across Omni, driving optimization leveraging Amazon Ads/DSP/AMC, Roku, iSpot, and Acxiom
      • Tackling CTV advertising in a closed-loop ecosystem with LiveRamp RampID
      • How AI impacts and influences CTV closed-loop advertising performance
      • Bottom line
  • Conclusion

Advice for the technology buyer

  • Advice for stakeholders
    • For media companies (publishers and platforms)
    • For advertisers (brands and agencies)
    • For technology buyers (ad tech and DSPs)

Learn more

  • Related research
  • Synopsis
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