What is direct response TV (DRTV)?

For years, marketers have worked around a familiar disconnect. Campaigns go live first. Measurement follows later. Insights arrive after audiences are reached, and budgets are committed. That gap has slowed decisions, blurred performance signals, and limited marketers’ ability to respond when it counts. In 2026, that model changes. Activation and measurement no longer operate as separate steps. They function as a single system, where insight informs action as campaigns unfold. Consistency across identity, data, and decision-making sits at the center of this shift, connecting the full campaign lifecycle from planning through outcomes. How is marketing measurement shifting from post-campaign reporting to in-flight intelligence in 2026? Marketing measurement in 2026 is moving from retrospective reporting to real-time input that shapes campaigns while they run. Instead of explaining performance after delivery, measurement now guides creative, audience, and channel decisions as verified outcomes appear. Historically, measurement worked like a post-mortem. Dashboards showed what happened after campaigns ended, or weeks after impressions were delivered. Those insights supported long-term planning but rarely influenced performance in the moment. That dynamic has changed. Today, marketers embed measurement directly into activation. Campaigns adapt while they run. Creative evolves based on engagement quality. Audience strategies adjust as verified outcomes come into view. Channel investments respond to performance signals, not assumptions. Connected ecosystems make this possible. Experian helps marketers plan, activate, and measure within a single framework by linking audiences, identity, and outcomes. When planning and performance live in the same environment, insight becomes actionable in the moment. Why is identity the connective layer between activation and measurement? Identity provides the consistent thread that links planning, activation, and outcomes into a unified system. Without it, marketers rely on proxy signals and disconnected views of performance. For years, fragmented identity frameworks made it difficult to connect media exposure to real-world outcomes. Without a consistent way to recognize audiences across planning, activation, and measurement, marketers relied on proxy metrics and modeled assumptions. That's changing as identity becomes interoperable across the ecosystem. Experian’s Digital and Offline Graphs help marketers onboard and resolve their data into a clean, connected foundation that supports everything that follows. From building audiences enriched with behavioral, demographic, and lifestyle insights, to activating those audiences across channels like connected TV (CTV), social, and programmatic through direct integrations with more than 200 platforms. When identity stays consistent from the first impression through final outcome, marketers gain a clearer view of what drives performance and where to act next. Our 2026 Digital trends and predictions report is available now and reveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in 2026. Download How does closed-loop measurement become standard in 2026? Closed-loop measurement is becoming the default as activation and measurement come together. Marketers now tie exposure directly to verified business outcomes instead of relying on inferred signals. In partnership with MMGY Global, we helped Windstar Cruises connect digital impressions directly to bookings. The result was more than 6,500 verified bookings and $20 million in revenue tied back to campaign exposure. That translated to a 13:1 return on ad spend. Download the full case study here This level of accountability changes how marketers optimize. Instead of relying on clicks or inferred intent, teams can measure outcomes that reflect business impact. Store visits. Purchases. Site activity. These signals now guide decisions while campaigns are live. Through curated private marketplace deals and supply-path optimization, Experian also helps reduce cost, and improve reach and performance. With Experian and Audigent operating as one, marketers gain access to scalable, privacy-conscious data solutions that support both addressability and accountability across the supply chain. What should marketers plan for as activation and measurement connect in 2026? Marketing teams should prepare for an operating model built around continuous feedback, unified systems, and verified outcomes. This shift changes how success is defined and managed. Marketers should plan for: Always-on feedback loops Real-time signals guide creative, audience, and channel decisions while campaigns are in flight. Unified planning, activation, and outcome validation Integrated identity and audience frameworks allow marketers to trace value across every impression, not just the last click. Outcome-based performance signals Measurement will focus less on surface-level performance and more on true business impact, including sales, bookings, and long-term value. Greater use of first-party data Connected first-party data supports consistent activation and outcome validation across channels. Whether you're activating your own data or reaching new audiences, Experian connects every stage of the campaign. From early planners to last-minute buyers, we help you show up in the moments that matter and prove what is working. The takeaway Marketing's next chapter centers on connection. As data systems unify, activation and measurement operate as one. Insight flows directly into action. Decisions are guided by intelligence, not delayed reporting. With Experian, marketers plan, reach, and measure in a connected cycle. Every impression is measurable. Every audience is accurate. Every decision is powered by data ranked #1 in accuracy by Truthset. To explore this trend and the others shaping marketing in 2026, download our 2026 Digital trends and predictions report. Download Ready to connect with our team? About the author Ali Mack VP, AdTech Sales, Experian Ali Mack leads Experian’s AdTech business, overseeing global revenue across the company’s expansive tech and media portfolio. With over a decade of experience in digital and TV advertising, Ali drives strategic growth by aligning sales, customer success, and solutions teams to deliver impactful outcomes for clients and partners. She has successfully guided teams through two major acquisitions, integrating sales organizations and product portfolios into unified go-to-market strategies. Under her leadership, Experian has consistently exceeded revenue targets while fostering collaborative, results-driven teams and mentoring emerging leaders. Working closely with finance, product, and marketing, Ali develops strategies that support a diverse ecosystem of publishers, brands, and technology partners, positioning Experian at the forefront of data-driven advertising and identity resolution. FAQS How is marketing measurement shifting from post-campaign reporting to in-flight intelligence in 2026? Marketing measurement in 2026 is moving from retrospective reporting to real-time input that shapes campaigns while they run. Instead of explaining performance after delivery, measurement now guides creative, audience, and channel decisions as verified outcomes appear. Connected ecosystems make this possible. Experian helps marketers plan, activate, and measure within a single framework by linking audiences, identity, and outcomes. When planning and performance live in the same environment, insight becomes actionable in the moment. Why is identity the connective layer between activation and measurement? Identity provides the consistent thread that links planning, activation, and outcomes into a unified system. Without it, marketers rely on proxy signals and disconnected views of performance. Experian’s Digital and Offline Graphs help marketers onboard and resolve their data into a clean, connected foundation that supports everything that follows. From building audiences enriched with behavioral, demographic, and lifestyle insights, to activating those audiences across channels like connected TV (CTV), social, and programmatic through direct integrations with more than 200 platforms. How does closed-loop measurement become standard in 2026? Closed-loop measurement is becoming the default as activation and measurement come together. Marketers now tie exposure directly to verified business outcomes instead of relying on inferred signals. In partnership with MMGY Global, we helped Windstar Cruises connect digital impressions directly to bookings. The result was more than 6,500 verified bookings and $20 million in revenue tied back to campaign exposure. That translated to a 13:1 return on ad spend. What should marketers plan for as activation and measurement connect in 2026? Marketers should plan for: always-on feedback loops, unified planning, activation, and outcome validation, outcome-based performance signals, and greater use of first-party data. Whether you're activating your own data or reaching new audiences, Experian connects every stage of the campaign. From early planners to last-minute buyers, we help you show up in the moments that matter and prove what is working. Latest posts

Claritas, known for advanced consumer segmentation, is bringing its premium audiences into Experian Data Marketplace. PRIZM® Premier, P$YCLE® Premier, ConneXions® Premier and CultureCode® audiences are now available, giving marketers access to more than 1,700 syndicated segments in a frictionless, privacy-compliant way. Marketers can move from planning to activation faster, with lifestyle, and financial audiences built for modern media. The value of these insights is clear: richer, behavior-driven audience intelligence that supports more relevant targeting across connected TV (CTV), digital, and linear. How Claritas audiences are built Claritas audiences are built from more than 10,000 predictive behavioral indicators, robust survey linkages, and household-level demographic data. These inputs create deterministic, privacy-safe signals that go beyond broad demographic proxies and help reveal consumer intent. That detail matters in CTV and programmatic environments. Marketers can activate pre-modeled segments tied to automotive ownership, financial behaviors, telecom preferences, and brand affinities. Three ways Claritas audience support omnichannel activation High-fidelity signals for more effective targeting Claritas uses deterministic, behavior-based indicators to add context around lifestyle, purchase patterns, financial posture and technology behaviors. Each segment includes Living Unit ID (LUID) counts, CPM transparency, and match-rate details. Broad reach across channels Many segments include 30M–50M+ active LUIDs, supporting broad reach without sacrificing audience clarity. Activate these audiences in omnichannel campaigns across the destinations that matter most, including CTV, programmatic display/video, paid social, and email, enabled through integrations with major demand side platforms (DSPs) and activation platforms. Privacy-first design Claritas data is built from consented, privacy-safe inputs and does not rely on cookies or exposed personally identifiable information (PII). This approach supports cookieless media, including CTV. Where Experian adds lift to audience activation Experian's data marketplace and our identity and governance tools help operationalize Claritas segments for activation:  Enhanced addressability: Deterministic identity resolution maps Claritas signals to reachable, active audiences. It utilizes Experian identity graphs, which are rooted in verified data, spanning 126 million U.S. households, 250 million individuals, and over four billion active digital identifiers. Activation: Integrations with major DSPs and media platforms support fast deployment. Governance: Our controls support responsible data handling through the activation workflow, and ensure available audiences comply to all federal, state, and local consumer privacy regulations. Together, Claritas segmentation depth and our identity resolution support audience planning, activation, and measurement at scale. How marketers use Claritas audiences Automotive: Connect with owners and intentenders A luxury automotive brand can target “Cadillac owners” or “Likely Luxury Intenders” using Claritas behavioral automotive indicators. With more than 42 million available LUIDs for Cadillac owners, original equipment manufacturers (OEM) can support CTV campaigns, conquest strategies, and multicultural initiatives with more confidence. Financial services: Reach high-value households Using P$YCLE® Premier, a card issuer can target consumers who actively use travel reward cards or who fall into specific wealth tiers. These insights help tailor offers, personalize messaging, and reach consumers more likely to convert, supported by Claritas’ AI-driven optimization that can increase conversions by up to 30%. The advantage: Claritas depth plus Experian scale Claritas audiences in Experian’s data marketplace give marketers a direct path from insight to activation. Claritas brings behavioral intelligence and segmentation depth and we bring identity, scale, and governance. Together, you can plan, activate, and measure campaigns with stronger audience clarity from day one. Contact us to get started FAQs What are Claritas audiences in Experian’s data marketplace? Claritas audiences are syndicated consumer segments built from behavioral, lifestyle, financial, and demographic data. Through Experian’s data marketplace, marketers can activate more than 1,700 Claritas segments using privacy-compliant, deterministic signals. Where can marketers activate Claritas audiences? Marketers can activate Claritas audiences directly through Experian’s data marketplace across CTV, programmatic display, social, email, and linear. Integrations with major DSPs and Experian identity resolution support privacy-compliant activation at scale. How are Claritas audiences built? Claritas audiences are built from more than 10,000 predictive behavioral indicators, survey-based insights, and household-level demographics. How does Experian support Claritas audience activation? Experian supports activation through identity resolution, governance controls, and direct platform integrations. Claritas signals are mapped to reachable audiences using the Experian identity graph.  Latest posts

Why AI data governance determines trust in automated decisions AI is reshaping audience strategy, media investment, and measurement. Automated systems now make more decisions at scale and in real time. Trust in those decisions depends on the data that informs them. AI data governance provides the framework that allows organizations to answer foundational questions like: Which information or inputs guided this decision? Is the model respecting consumer rights? Could bias be influencing the outcome? If AI made the wrong call, how would we know? Without governed data, these questions remain unanswered. AI data governance creates accountability by establishing quality controls, consent validation and auditability before data enters automated systems. Most organizations are still building their readiness to govern data at scale. Many vendors highlight “fast insights” or “transparent reporting,” but few can support true data governance — the auditability, privacy-by-design, quality controls, and continuous compliance required for responsible AI. That foundation is where responsible automation begins. And it’s why trust in AI starts with data governance. Responsible automation begins with governed data Automation produces reliable outcomes only when data is accurate, current, consented and interoperable. AI data governance makes responsible automation possible by applying controls before data reaches models, workflows, or activation channels. AI systems may interpret context, predict signals, and act in real time. But no model, logic layer, or LLM can be responsible if the data feeding it isn’t governed responsibly from the start. This raises a core question: How do we ensure AI systems behave responsibly, at scale, across every channel and workflow? The answer begins with trust. And trust begins with AI data governance. Governing the data foundation for responsible AI Experian’s role in AI readiness begins at the data foundation. Our focus is on rigorously governing the data foundation so our clients have inputs they can trust. AI data governance at Experian includes: Model governance reviews before releasing new modeled attributes Feature-level checks ensuring no prohibited or sensitive signals are included Compliance-aware rebuilding and re-scoring, incorporating opt-outs and regulatory changes Validated delivery, ensuring attributes reflect the most current opt-outs, deletes, and compliance requirements By governing data at the source, we give our clients a transparent, accurate, and compliant starting point. Clients maintain responsibility for bias review within their own AI or LLM systems — but they can only perform those reviews effectively when the inputs are governed from the start. This is how AI data governance supports responsible automation downstream. Our 2026 Digital trends and predictions report is available now and reveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in 2026. Download Privacy-by-design strengthens AI data governance Privacy gaps compound quickly when AI is involved. Once data enters automated workflows, errors or compliance issues become harder, and sometimes impossible, to correct. AI data governance addresses this risk through privacy-first design. Experian privacy-first AI data governance through: Consent-based, regulated identity resolution A signal-agnostic identity foundation that avoids exposing personal identifiers Ongoing validation and source verification before every refresh and delivery Compliance applied to each delivery, with opt-outs and deletes reflected immediately Governed attributes provided to clients, ensuring downstream applications remain compliant as data and regulations evolve Experian doesn’t govern our client’s AI. We govern the data their AI depends on, giving them confidence that what they load into any automated system meets the highest privacy and compliance standards. Good data isn’t just accurate or fresh. Good data is governed data. How AI data governance supports responsible automation at scale With AI data governance in place, organizations can build AI workflows that behave responsibly, predictably, and in alignment with compliance standards. Responsible automation emerges through four interconnected layers: 1. Input Privacy-first, governed data: accurate, consented, continuously updated, and compliant. 2. Enrichment Predictive and contextual insights built from governed data, ensuring downstream intelligence reflects current and compliant information. 3. Orchestration Reliable, AI-powered workflows where governed data inputs ensures consistency in audience selection, activation, and measurement at scale. 4. Guardrails Transparent, responsible innovation. Clients apply their own model governance, explainability, and oversight supported by the visibility they have into Experian’s governed inputs. Together, these layers show how data governance enables AI governance. AI integrity starts with AI data governance Automation is becoming widely accessible, but responsible AI still depends on governed data. Experian provides AI data governance to ensure the data that powers your AI workflows is accurate, compliant, consented, and refreshed with up-to-date opt-out and regulatory changes. That governance carries downstream, giving our clients confidence that their automated systems remain aligned with consumer expectations and regulatory requirements. We don’t build your AI. We enable it — by delivering the governed data it needs. Experian brings identity, insight, and privacy-first governance together to help marketers reach people with relevance, respect, and simplicity. Responsible AI starts with responsible data. AI data governance is the foundation that supports everything that follows. Get started About the author Jeremy Meade VP, Marketing Data Product & Operations, Experian Jeremy Meade is VP, Marketing Data Product & Operations at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies. FAQs about AI data governance What is AI data governance? AI data governance is the framework that manages data quality, consent, compliance and auditability before data enters AI systems. Why does AI data governance matter? AI decisions reflect the data used as inputs. Governance provides transparency, accountability and trust in automated outcomes. Does AI data governance prevent bias? AI data governance does not eliminate bias in models. It provides governed inputs that allow organizations to identify and address bias more effectively. How does privacy-first design support AI data governance? Privacy-first governance applies consent validation and compliance controls before data is activated, reducing downstream risk. Who is responsible for AI governance? Organizations govern their AI systems. Data providers govern the data foundation that feeds those systems. Latest posts