At A Glance
AdRoll and Experian help marketers grow the full funnel by combining audience data, identity resolution, and connected TV (CTV) measurement. Marketers can reach new prospects, retarget across screens, and measure CTV's impact on website visits, keeping strategic decisions in human hands as AI takes on more optimization tasks.Key takeaways
- eMarketer forecasts that U.S. advertisers will spend more on connected TV ($17.73 billion) than primetime linear TV ($16.98 billion) in 2026.
- AdRoll’s Household Reach & Site Visit report, built on Experian’s Digital Graph, links CTV exposure to later website visits at the household level.
- Marketers can access Experian Audiences and Experian Audience Engine directly inside AdRoll’s campaign workflow without a separate data integration.
- AdRoll recommends a clear AI framework: people set the what and why, while AI manages the how and how much of campaign execution.
Finding new customers is only part of the challenge. Marketers also need to reach the right people across CTV and digital channels, then understand what happens after the first impression.
Will Nixon, Head of Data Partnerships at AdRoll, joined us to discuss how Experian Audiences and cross-device identity help marketers fill the funnel, prove CTV’s impact on the customer journey, and keep people in charge of strategy as AI takes on optimization.
Reach, accuracy, and proof don’t always move together
Growth marketers must balance scale, relevance, and proof. Layer too many audience segments and reach shrinks; go too broad and relevance suffers. CTV adds a measurement challenge because viewers can’t click the ad, leaving last-click attribution unable to capture the full journey.
That matters as CTV attracts more investment. For the first time, eMarketer forecasts that U.S. advertisers will commit more of their upfront TV budgets to CTV ($17.73 billion) than to primetime linear TV ($16.98 billion) in 2026.
As more budget moves to CTV, the pressure to prove it’s working grows with it. Marketers need to reach the right people consistently, then connect ad exposure to what happens next. That’s where the AdRoll and Experian partnership comes in: Experian’s audience data brings new prospects into the funnel, AdRoll’s long track record in retargeting keeps the conversation moving toward purchase, and a durable identity layer connecting the journey across screens.
Building the funnel on Experian data, inside AdRoll
AdRoll gives marketers access to Experian audience data right inside the campaign workflow, so they can plan and activate campaigns without a separate data integration.
Together, these capabilities help marketers move from understanding an audience to reaching it, then connect campaign activity across devices.
Connecting the big screen to what happens next
CTV gives marketers a powerful way to reach people, but the lack of a click can make it difficult to connect an ad exposure directly with later engagement.
AdRoll’s Household Reach & Site Visit helps marketers connect CTV exposure with later website engagement. Built on our identity graph, the report shows how many households a CTV campaign reached and how many of those households visited the marketer’s website after ad exposure.
That links two parts of the journey: CTV exposure and later website engagement from a digital device in the same household.
“This gives our sellers and our customers confidence to reinvest in CTV, because before this they were a little bit flying blind: we invested in CTV, we ran all these ads, but what was the impact of that? This helps tell that story.”
AdRollWill Nixon, Head of Data Partnerships
Where people stay in charge as AI takes on more campaign optimization
Even with AI handling more of the work, marketers still need to decide who leads and where the technology can help. AdRoll uses a simple framework: people own the what and why, and AI owns the how and how much.
People define the business outcomes and creative guardrails. AI can recommend how to allocate budgets across channels, measure performance, and learn from campaign data. The more of those decisions AI makes, the more data quality, governance, transparency, and marketer control matter.
“Humans own the what and the why: what are we trying to achieve for customers, and why does it matter to them? AI owns the how and how much: how are we going to reach the users, how much are we going to spend on each channel, and how are we going to measure it?”
AdRollWill Nixon, Head of Data Partnerships
This is also why the AdRoll and Experian relationship matters; Experian’s audience data and identity resolution give AdRoll a trusted, well-governed foundation, so marketers can rely on the data behind the how and how much while they stay focused on the what and why.
What this means for your next campaign
If you’re planning a full-funnel program, start with four questions:
Together, AdRoll and Experian help marketers connect audience understanding, activation, identity, and measurement across more of the customer journey.
Ready to grow your funnel with Experian and AdRoll?
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About our expert
Will Nixon
Head of Data Partnerships, AdRoll
Will Nixon is the Head of Data Partnerships at AdRoll, where he leads the commercial strategy for the company’s audience targeting and identity data products. A 15-year AdTech veteran, Will also leads supply path optimization strategy at AdRoll, as well as publisher development at Virool and Brand.net. Will also enjoys spending time in the mountains or the ocean while he awaits the 50-year storm.
FAQs
Experian’s Digital Graph connects mobile advertising IDs and CTV IDs to households, giving AdRoll’s Household Reach & Site Visit report the identity layer it needs. This lets marketers see how many households a CTV campaign reached and how many of those households later visited their website, closing a gap that last-click attribution can’t cover.
Experian Audiences are thousands of ready-to-use, syndicated segments covering demographics, financial profiles, intent, interests, and purchase behavior that marketers can select directly inside AdRoll. Experian Audience Engine works differently by letting marketers combine their own first-party data, such as an email list, with Experian’s Marketing Attributes to build a custom modeled audience when a syndicated segment isn’t the right fit.
CTV is harder to measure because viewers can’t click the ad, so last-click attribution models can’t capture the full path to a later action. That’s why household-level identity resolution, like the kind Experian’s Digital Graph provides, is necessary to connect a CTV ad exposure to what a household does next.
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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