At A Glance
With Experian’s Digital Graph, a leading DSP resolved 84% of IDs and increased match rates across digital channels such as CTV and display. The result: stronger attribution, clearer ROI proof, and renewed client confidence.Demand-side platforms (DSPs) are more than just technology providers, they’re strategic partners, helping marketers answer the key question: “How should I spend my media budget?”
A leading DSP struggled to attribute consumer actions across digital channels such as connected TV (CTV) and display. Without connecting impressions to conversions, they risked losing client trust and ROI proof. With Experian’s Digital Graph, they resolved 84% of IDs and increased match rates, strengthening attribution and client confidence.
The challenge
A leading DSP had trouble showing which ads drove results across CTV, display, and digital. Without linking ad views to conversions, they couldn’t prove ROI.
The missing piece was attribution. They needed to show which channels drove conversions, but without strong identity resolution, it was hard to connect CTV ads to website activity.
What is Experian’s Digital Graph?
Built from trillions of real-time data points and updated weekly, Experian’s Digital Graph connects billions of identifiers across devices and households, such as cookies, mobile ad IDs (MAIDs), CTV IDs, IP addresses, universal IDs, and more. It gives DSPs a reliable foundation by linking these identifiers back to households and individuals, improving DSPs’ ability to offer attribution by better connecting impressions to conversions.
What makes the Digital Graph unique is its scale and freshness. It ingests trillions of signals in real time and delivers updates weekly. That consistency matters: it gives DSPs confidence that they’re working with the most accurate view of digital identity.
AI and machine learning (ML) are core to how we maintain that level of accuracy. Our models use sophisticated clustering algorithms to analyze device connections at both household and individual levels. By evaluating data points such as timestamps, IP addresses, user agents, cookie IDs, and device identifiers, these algorithms create precise device groupings that enhance targeting and measurement accuracy. The models are continuously refined, ensuring our clients can better understand consumer behaviors within households and activate more effective, personalized marketing.
Think of it like connecting puzzle pieces scattered across devices and channels. On their own, each piece doesn’t say much. Together, they reveal the full picture of who saw an ad, engaged, and converted, and which ads performed best.
The solution
This expanded identity universe gave the DSP a unified view of individuals and households, making it possible to connect impressions to conversions across devices and channels. With each weekly refresh, attribution models stayed accurate and up to date, turning fragmented signals into proof of performance.
Results
With a stronger foundation of digital identifiers, the DSP matched more MAIDs, CTV IDs, and IP addresses to conversions. This allowed them to show clients exactly which ads and channels drove ROI, transforming impression reports into actionable proof of performance and strengthening client trust.
Why attribution matters now
Attribution has never been more critical. With signals fading and marketing budgets under pressure, DSPs need reliable data to prove performance.
Experian’s Digital Graph takes a multi-ID, always-on approach, refreshed weekly with trillions of signals. This delivers consistency and accuracy that single-point, stale-ID solutions can’t match.
For this DSP, that meant transforming attribution from guesswork into clear proof, strengthening client trust, and proving ROI across channels.
Connect with us today to see how our Digital Graph can help you maximize advertiser trust and ROI.
Ready to strengthen your approach to attribution?
FAQs
Experian’s Digital Graph is a privacy-conscious identity resolution solution built from trillions of real-time data points, refreshed weekly, that links identifiers like cookies, MAIDs, CTV IDs, Unified I.D. 2.0 (UID2), ID5 IDs and IP addresses to households and individuals.
Experian’s Digital Graph improves attribution by connecting impressions to conversions across devices and channels, giving DSPs a clearer view of which ads and channels drove results.
While many platforms rely on single, static IDs, Experian’s Digital Graph uses a multi-ID, always-on approach with weekly refreshed, ensuring accuracy even as signals shift.
When you use Experian’s Digital Graph, you can expect higher match rates, more synced IDs, clearer attribution models, and stronger proof of ROI for your clients. Because Experian’s Digital Graph serves as the backbone of the industry, it also helps DSPs maximize the scale and reach they can deliver to advertisers.
Yes. Experian’s Digital Graph is designed with privacy in mind, ensuring compliance while still delivering accurate attribution insights.
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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