Originally appeared in MarketingProfs
We all understand the importance of data quality. Metrics like third-party validations, match rates, and accuracy scores help us assess data quality on its own terms. Yet too often, organizations struggle to connect high-quality data with real-world business outcomes. How does data accuracy directly impact the ability to reach target audiences and campaign performance?
Scale and cost: The tradeoffs of accuracy
Marketers are frequently incentivized to prioritize broad reach, even at the expense of precision. This often leads to decisions driven by short-term gains—reaching more people at a lower cost. The temptation is deceptively straightforward, but deep down we know overly simplistic approaches are likely to fall short.
Cheaper data solutions, even if they seem to provide greater reach, mask a deeper issue. The data may not be accurate. In fact, the initial savings from cheaper data typically result in higher long-term costs due to inefficiencies and waste that are hard to track. Unless you’re carefully evaluating your campaign results, it can be difficult to see where the inefficiencies are creeping in.
The hidden cost of inaccurate data
Programmatic platforms make it easy for mistargeted impressions to slip through unnoticed. Common issues include:
Direct mail waste is tangible: towering stacks of returned mail serve as undeniable reminders of inefficiency, not to mention the financial costs of wasted postage. Digital campaigns, by contrast, often obscure their inefficiencies within complex programmatic platforms or impression reports. It’s like watching a gust of wind scatter piles of paper into the ether—it’s hard to track and quantify.
As a result of these data inaccuracies, brands mistakenly assume they’re optimizing their budgets when, in fact, they’re hemorrhaging money and reaching the wrong people with a message they don’t care about. It’s a marketer’s nightmare scenario.
The perceived savings from cheaper, less accurate data turn out to be an illusion.
The compounding effect of inaccurate data
Consider a situation where an inaccurate insight or signal prompts a brand to adjust its targeting toward an underperforming segment. Each new campaign uses this flawed data to guide its optimizations, amplifying the waste. What starts as a minor inefficiency quickly becomes a significant budget drain, funneling resources into segments that aren’t delivering.
If you bake a cake but use salt instead of sugar–each new ingredient only makes the final product more unpalatable. With ad targeting, the feedback loop created by optimization tools exacerbates this issue. Decisions are made based on misleading metrics, perpetuating flawed strategies and causing brands to over-invest in underperforming tactics. Without scrutiny, brands risk building entire strategies on fundamentally flawed insights.
The value of investing in the highest quality data
Acting on what the data tells you
Collecting accurate data is just the first step—the real challenge is having the ability to act on what it reveals. Many brands enter campaigns with preconceived notions about their target audience, only to find the data tells a different story. Ignoring these insights stifles growth. The value of data-driven marketing lies in trusting the insights and adapting strategies accordingly.
How to test if your current approach is working
We understand that changing data providers can feel daunting, but there are low-lift ways to explore whether your current approach is truly delivering. Test the waters by selecting an Experian Audience on a major platform or building a custom audience to see how your campaigns perform. Alternatively, collaborate with Experian’s insights team to gain a deeper understanding of your audience and determine if it aligns with your current strategy. It’s a small step that could lead to a big impact.
Get in touch with our team today
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
Reach buyers based on how they shop in a changing market. Experian Audiences help target switchers, align to budgets, and match messaging to inventory.
Explore how Experian utilizes AI to power data-driven programmatic advertising with greater accuracy, efficiency, and consumer trust.