At A Glance
Real-time data enrichment (RTDE) helps programmatic campaigns use fresh bid-time signals when ad placement decisions are made. This article explains how RTDE works, why signal freshness matters for agentic media buying, and how Experian help marketers connect identity, audience packaging, curation, and measurement.Programmatic needs decisions grounded in trusted signals available at the moment a bid is made. As campaigns lean further into automation and agentic media buying, real-time data enrichment (RTDE) gives marketers a way to compute derived, bid-time signals during the ad placement process. That can cut latency, reduce unnecessary data movement, and keep media decisions tied to current conditions rather than delayed inputs.
This matters as identity, data collaboration, and measurement become core marketing infrastructure. Marketers need signals they can trust, partners that work across the ecosystem, and enough flexibility to keep control as buying systems become more automated.
How does RTDE work in programmatic advertising?
In programmatic advertising, RTDE works by computing useful signals inside the auction path before a bid is placed. The goal is to give bidding systems more current inputs without moving raw data through a long chain of vendors.
When a bid request fires, RTDE computes derived signals, such as validated identity attributes, cohort scores, or context flags, inside the auction window and passes those signals to the bidder. Instead of sending raw data through a long chain of vendors and hoping it is still useful by the time it’s used, RTDE runs closer to the supply-side source and sends the output needed for the bid.
That gives you a more current view of what’s happening in market, from regional demand shifts, to seasonal patterns, to live inventory changes. It can make first-party activation more responsive and keep programmatic decisions closer to the moment media is bought.
For brands, agencies, publishers, and platforms, this creates a more flexible way to use data across partners without sending raw inputs through every step of the workflow.
How does RTDE improve programmatic performance?
RTDE improves programmatic performance by helping close gaps between available data and the bid-time decision. It gives campaigns signals that are current, consistent, and usable across auctions. These gains can help put budget against impressions with a stronger basis for action, which matters most in categories where timing and relevance shape performance.
It can also give teams a clearer way to connect data quality, identity, and measurement decisions across different activation paths.
RTDE improves programmatic performance by focusing on:
Why does signal freshness matter in agentic buying?
Signal freshness matters in agentic buying since software agents make autonomous decisions in real time. Without fresh, accurate signals, these agents risk acting on outdated or incomplete information. As AI takes on more campaign decisions, the quality of the consumer data, identity layer, and governance behind those decisions becomes even more important.
Outdated signals can lead to missed opportunities, such as failing to capitalize on sudden spikes in demand or changes in consumer behavior. Fresh signals ensure that campaigns remain agile and responsive, even in fast-changing market conditions.
Signal freshness is critical because it ensures:
What makes Experian a trusted partner in RTDE?
Experian is a trusted partner in RTDE because we bring together independent identity, audience data, broad media partner integrations, and governance. That combination enables marketers to use bid-time enrichment responsibly and connect programmatic decisions to measurable outcomes.
We work across the advertising ecosystem, not inside one closed environment. That independence helps marketers maintain choice across agencies, platforms, publishers, commerce media networks, clean rooms, and measurement partners.
Our identity solutions help you build a flexible foundation for programmatic advertising across planning activation, curation, and measurement. With access to over 5,000 behavioral, demographic, and lifestyle attributes, we ensure a richer understanding of audiences.
We prioritize data governance and security, handling sensitive information responsibly to maintain privacy-forward solutions.Integrations with over 200 media partners make it easy to activate addressable audiences and improve campaign performance. We’re focused on making enrichment more immediate and usable at bidding time through timely, trustworthy, and governable signals.
That combination matters as AI agents and marketing systems rely on consumer data to make faster decisions. The stronger the identity, governance, and data stewardship behind those systems, the more confidence teams can have in how decisions are made.
Experian helps marketers build actionable programmatic strategies
We can help you build actionable programmatic strategies by connecting identity, audience packaging, curation, and measurement into one cohesive foundation. This foundation makes ad placements easier to execute and measure, while reducing friction between planning and activation. We can help you build audience packages and curated deals that align with your campaign goals. This gives marketers a flexible identity foundation that can adapt as partner needs, channel plans, and data collaboration models change.
You can activate addressable audiences across advanced TV, social, and programmatic platforms, then measure how campaigns connect to consumer behavior and real-world outcomes. Our capabilities give teams a clearer path from planning to activation to measurement.
A strong RTDE strategy connects activation with governance, measurement, and transparency, giving teams a clearer view of how audiences are built, where they’re used, and how outcomes are evaluated.
Get started with real-time data enrichment
Real-time data enrichment signals are only valuable when they can be used at the moment decisions are made. We bring timely, trustworthy signals into the programmatic workflow so your campaigns can respond to current conditions.
As the market changes, marketers need identity and data partners that protect control, preserve choice, and make trusted data usable across the full programmatic workflow.
Connect with us to discuss how real-time data enrichment can support your programmatic strategy.
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About the author
Matthew Griffiths
SVP of Technology, Audigent, a part of Experian
Matthew Griffiths is a seasoned technology entrepreneur and a driving force in advertising technology, data technology, and AI. As the Co-Founder and former CTO (now SVP of Technology) at Audigent, a part of Experian, he plays a pivotal role in shaping the company’s cutting-edge solutions for data activation, curation, and identity management.
With years of executive experience across the U.S., Africa, and the U.K., Matthew has a proven track record of leadership in steering the adoption and use of cutting-edge technologies to drive business outcomes. His expertise spans from collaborating with top global corporations and governments to spearheading award-winning technology projects that deliver life-changing impacts in some of the world’s most underserved communities.
Matthew’s dynamic approach to solving complex business and technology challenges makes him a visionary leader in the AdTech space, consistently driving innovation and performance through technology.
FAQs
Real-time data enrichment is the process of computing derived signals during the bid request process, before an ad placement decision is made. In programmatic advertising, it helps bidding systems use current signals, such as identity attributes, cohort scores or context flags, instead of relying only on delayed inputs.
Real-time data enrichment helps media buyers make bid decisions with fresher, more consistent signals. That can improve how campaigns respond to demand shifts, seasonal patterns, inventory changes, and conversion behavior.
Real-time data enrichment matters for agentic media buying since autonomous agents need current, reliable signals to make sound decisions. If the signals are stale or incomplete, agents can miss changes in demand, inventory, or audience behavior that affect campaign outcomes.
Experian’s identity foundation helps marketers resolve and validate the signals that support real-time data enrichment. Experian’s data, privacy-forward approach, and integrations with more than 200 media partners help marketers activate addressable audiences and connect programmatic decisions to measurable outcomes.
Latest posts
In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
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