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:
Stale data, where consumer behaviors and locations have changed but the data hasn’t.
Inactive signals, where you think a digital identifier like a device ID is addressable, but the device hasn’t been used in months.
Disparate or duplicative data, where you think you’re reaching three people but in fact it’s just one person who you’re frequency bombing. Nobody likes getting the same ad over and over again. It’s like if your co-worker messaged you “hey” five times in a row.
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
With accurate data, brands can zero in on the right audience. This is particularly critical in lookalike modeling. By enriching customer files, brands can understand the nuances of who their best customers are—and how to find more of them. Tailored messaging, based on a consumer’s actual behaviors and interests, deepens engagement. Conversion rates rise as campaigns meet customer needs.
Accurate data also provides insights that aren’t immediately obvious. Sometimes, seemingly minor behaviors or unexpected demographic segments can emerge as key drivers of conversions. It’s like finding the one avocado at the grocery store that’s perfectly ripe…you’re well on your way to delicious guacamole.
To truly grasp the impact of data accuracy, traditional validation metrics such as third-party assessments (e.g. Truthset) should be paired with other performance indicators that show you how well data reflects actual consumer behavior. With this complete picture in view, the choice is obvious: quality data is worth the premium.
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
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Audigent, a part of Experian, was named Microsoft Advertising’s Curator of the Year. The honor recognizes Audigent’s leadership for advancing privacy-safe, sell-side curation that packages high-quality audiences with premium supply for measurable campaign performance. Once only a buzzword, curation has become a mainstream strategy for activating advertisers’ first-party data and streamlining programmatic buying. To recognize this shift and the leaders driving it, Microsoft introduced Curate and established the Curator of the Year award to celebrate excellence in this category. Audigent was recognized for: End-to-end curation from audience planning through activation for outcomes-based, closed-loop programs. Breadth of deal and supply types using unique datasets, real-time supply connections and always-on optimization. Data-driven activation with curation across a large publisher footprint that utilizes Experian marketing data, first-party data, and partner audiences. Audigent’s unique, contextual, and predictive audience data solutions are built into all programmatic media buying. The combination of Audigent’s Real-Time Data and Curation Platform and first-party data, along with Experian identity and optimization, turns real engagement into ready-to-activate audiences. These audiences are available within Microsoft Curate and across omnichannel buying. \”Audigent is proud to be named Microsoft Advertising’s Curator of the Year. This is a clear validation of the work our team has done to make curation the new standard in data-driven programmatic activation. We will continue to set the standard by expanding curated deals in Microsoft Curate. This will help maximize efficiency across the bidstream.”Chris Meredith, Head of Supply Side Partnerships Together, Experian and Audigent connect identity to inventory, enabling advertisers to reach the right audiences with precision and scale. By harnessing Experian identity and audience solutions and activating Audigent-curated deals in Microsoft Curate, brands can unlock new levels of efficiency and performance across every programmatic channel. This recognition sets the stage for even greater innovation, collaboration, and results in the year ahead. Ready to design your curated library? Let\’s connect Latest posts
How third-party data has changed and why it matters in 2025 For years, third-party data operated in an expansive, lightly regulated marketplace: fast-moving, high-growth, and filled with players eager to capitalize on digital marketing’s demand for audience insights. That era is over. Regulatory scrutiny, stricter compliance standards, and rising consumer expectations have already transformed the market. Today, third-party data belongs to partners with proven expertise and built-in compliance. This isn’t a space for opportunistic newcomers; it’s one that rewards long-term commitment and trust. Even the rapid rise of retail media networks (RMNs) reflects this shift. These platforms are built on long-standing, trusted relationships between brands, retailers, and data partners, utilizing that foundation in new ways to reach audiences responsibly and effectively. The best providers have already made this transition; those still “shifting” are catching up. From growth to governance: A market defined by accountability The third-party data ecosystem has matured. After years of rapid expansion and recalibration, the market has stabilized around a new standard: data quality and regulatory accountability. Third-party data enriches first-party insights with attributes such as income, gender, and interests that round out the customer view. But when the industry grew unchecked, unreliable providers diluted quality and trust. This resulted in a decline in the overall value and reliability of the third-party data marketplace. That breakdown led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Does third-party data still matter in a privacy-first era? Third-party data isn’t disappearing, if anything, it’s become more important. Brands will always need additional insight to deepen customer understanding; first-party data alone only reflects what’s already known. The industry has entered a mature phase where data quality and compliance are table stakes. The companies leading today built their data infrastructure on rigorous standards, regulatory foresight, and transparent governance. That same foundation powers the next wave of innovation, including the explosive growth of RMNs. RMNs rely on responsibly sourced third-party data to enrich shopper insights, validate audiences, and extend addressability beyond their own walls. Trusted data partners make that expansion possible, connecting retail environments with broader media ecosystems while maintaining privacy and accuracy. High-quality, compliant third-party data remains essential because it: Fills knowledge gaps Good third-party marketing data complements first-party insights with demographic, behavioral, and transactional context, providing the missing puzzle pieces to complete the full customer profile. Improves accuracy Filling in gaps in customer understanding helps you identify, reach, and engage your customers more effectively. This helps improve the delivery of relevant messages and offers to your customers and prospects across channels. Builds connections Third-party data helps brands build loyalty with consumers by speaking to their interests, and intent behind purchases. Fuels prospecting Third-party data can help you find your best prospects. By enriching customer files, you can understand who your best customers are, and how to find more of them. By modeling this data, you can determine who your best customers are and source prospects similar to them. Advancements in AI and machine learning are reshaping how this data is used across the ecosystem. What was once primarily a buy-side tactic is now expanding into the sell-side, where publishers and platforms are using data to curate, package, and activate audiences more intelligently. As AI enhances modeling accuracy and automation, third-party data will play an even greater role in connecting brands and consumers in more meaningful, privacy-conscious ways. The bottom line: it’s not about having more data; it’s about having better, verified data you can trust. How can you spot a trustworthy data partner? The strongest third-party data partners demonstrate accountability through experience, infrastructure, and integrity. Swipe right on the perfect data partner Look for providers that: Operate with clear data principles Trustworthy partners publish and follow codified data principles that guide every step of data handling. Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. Treat new privacy regulations as routine For mature providers, evolving privacy laws are routine, not disruptive. At Experian, privacy and compliance have long been built in. Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws. Decades of experience have shaped processes that emphasize risk mitigation, transparency, and accountability. Stay deeply connected Leading data companies maintain deep relationships with technology partners and industry and regulatory groups to ensure that ethical data practices are put into practice and their customers are aware of platform-specific regulations. Experian\’s relationships with demand-side platforms (DSPs), supply-side platforms (SSPs), and even social platforms like Meta, ensures we are aware of any platform-specific initiatives that may impact audience targeting. We’re also active participants in many trade groups to ensure that the industry puts ethical data practices in place to ensure consumers still receive personalized experiences but their data usage and collection is opt-in, transparent and handled with their privacy at the center of the transaction. Have a proven track record in the industry Longevity matters in a regulated and compliance-driven industry. Providers that have thrived through economic cycles and regulatory shifts are the ones equipped for the future. 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Work with the company that’s setting the standard for responsible data-driven marketing and helping brands connect with people in meaningful, measurable ways. 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 What is third-party data? Third-party data is information collected by organizations that don’t have a direct relationship with the consumer. It supplements first-party data by adding demographic, behavioral, and interest-based insights. Why are privacy regulations reshaping data practices? Privacy regulations are reshaping data practices because consumers expect control over how their information is used. That expectation led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Laws like the CCPA and state-level privacy acts enforce this expectation, holding brands and data providers accountable for the ethical use of data. Can brands still use third-party data safely? Yes, brands can still use third-party data safely when sourced responsibly. Partnering with established, compliant providers like Experian ensures both legal protection and data accuracy. 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See how Experian\’s Digital Graph improved attribution accuracy for a demand-side platform (DSP) with 84% of IDs resolved Just because it is deterministic, doesn’t mean it’s highly accurate. You still need to refine and validate your data to make sure it tells a consistent story. You need to anchor your data around real people. Calculate the real impact of data accuracy Why does AI need fresh data? Outdated data can’t predict tomorrow’s behavior. AI thrives on recency. At Experian, our audiences are refreshed continuously to mirror real-world signals, from purchase intent to media habits, so every campaign reflects what’s happening now, not six months ago. And we don’t just advocate for fresh data, we rely on it ourselves. Our own AI-powered models, used across our audience and identity platforms, are continuously retrained on the most current, consented signals. This allows us to see firsthand how freshness drives better accuracy, faster optimization cycles, and more relevant outcomes. But freshness alone isn’t enough. With predictive insights, our models go beyond describing the past. They forecast behaviors, fill gaps with inferred attributes, and recommend next-best audiences, helping you anticipate opportunity before it happens. Fresh and predictive data means you’re reaching people in the moment that matters and shaping what comes next. With AI, that’s what defines performance. Explore Experian\’s most popular audiences, ready to activate now How do consent and governance build trust in AI? Responsible AI starts with responsible data. With 20 U.S. states now enforcing privacy laws, data compliance isn’t optional, it’s operational. At Experian, privacy and compliance are built in. Every data signal, attribute, audience, and partner goes through our rigorous review process to meet federal, state, and local consumer privacy laws. With decades of experience in highly regulated industries, we’ve built processes that emphasize risk mitigation, transparency, and accountability. Governance isn’t just about regulation, it’s also about innovation done right. We drive transparent and responsible innovation through safe, modular experimentation, from generative applications to agentic workflows. By balancing bold ideas with ethical guardrails and staying ahead of evolving legislation, we ensure our innovations protect consumers, brands, and the broader ecosystem while moving the industry forward responsibly. Compliance and governance aren’t just boxes to check; they’re the foundation that gives AI its license to operate. How does interoperability enable AI’s full potential? AI delivers its best insights when data connects seamlessly across fragmented environments. 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Our AI-powered models surface connections, recommend audiences, and uncover insights that would take humans months to find. But our experts shape the process, crafting the right inputs, ensuring data quality, reviewing model outputs, and refining recommendations based on industry knowledge and client goals. It’s this partnership between advanced AI and experienced people that turns predictions into actionable, trustworthy solutions. What “good data” looks like in action “Good data” becomes most powerful when it’s put to work. At Experian, our marketing data and identity solutions help brands and their partners connect accurate, consented, and interoperable data across the ecosystem, turning insight into measurable outcomes. Learn more about Experian\’s data solutions Learn more about Experian\’s identity solutions When Windstar Cruises and their agency partner MMGY set out to connect digital media spend to real-world bookings, they turned to Experian’s marketing data and identity solutions to close the attribution loop. By deploying pixels across digital placements and using Experian’s identity graph to connect ad exposure data with reservation records, we created a closed-loop attribution system that revealed the full traveler journey, from impression to confirmed booking. The results were clear: 6,500+ bookings directly tied to digital campaigns, representing more than $20 million in revenue, with a 13:1 ROAS and $236 average cost per booking. Attributed audiences booked $500 higher on average, and MMGY’s Terminal audience segments powered by Experian data achieved a 28:1 ROAS. This collaboration shows that responsible, high-quality data and AI-driven insights don’t just tell a better story; they deliver measurable business performance. Download the full case study How to choose the partner built for responsible AI Why the future of AI depends on “good” data The next phase of AI-driven marketing won’t be defined by who has the most data, but by who has the best. Leaders will: Operate with clear data principles grounded in transparency and truth Build consent and compliance into every workflow Keep data accurate, current, and interoperable Pair automation with human oversight AI success starts with good data. And good data starts with Experian, where accuracy, privacy, and purpose come together to make marketing more human, not less. Partner with Experian for AI you can trust About the author Budi Tanzi, VP, Product, Experian Budi Tanzi is the Vice President of Product at Experian Marketing Services, overseeing all identity products. Prior to joining Experian, Budi worked at various stakeholders of the AdTech ecosystem, such as Tapad, Sizmek, and StrikeAd. During his career, he held leadership roles in both Product Management and Solution Engineering. Budi has been living in New York for almost 11 years and enjoys being outdoors as well as sailing around NYC whenever possible. FAQs What defines “good data” according to Experian? At Experian, we define \”good data\” as the balance of accuracy, consent, freshness, and interoperability. We apply rigorous governance, validation, and cleansing across every signal to ensure that AI systems learn from real-time behaviors, not assumptions. This approach turns data into a foundation for reliable, ethical, and high-performing intelligence. How does Experian ensure AI-ready data accuracy? Experian ensures AI-ready data accuracy through advanced cleansing, conflict resolution, and human anchoring. Experian ensures AI models rely on verified, high-quality inputs. Experian\’s data is ranked #1 in accuracy by Truthset. Can Experian help brands stay compliant with privacy laws? Yes, Experian can help brands stay compliant with privacy laws. Experian’s privacy-first governance framework integrates ongoing audits, legal oversight, and consent management to ensure compliance with all federal, state, and global privacy laws. Compliance isn’t an afterthought; it’s embedded in every step of our data lifecycle. How does Experian make AI more human? Experian makes AI more human by pairing innovation with human oversight to ensure AI helps marketers understand people, not just profiles. At Experian, we believe the future of marketing is intelligent, respectful, and human-centered. AI has long been part of how we help brands connect identity, behavior, and context to deliver personalization that balances privacy with performance. Our AI-powered solutions combine predictive insight, real-time intelligence, and responsible automation to make every interaction more relevant and ethical. Where can marketers access Experian’s high-quality data? Marketers can activate Experian\’s high-quality data directly in Experian’s Audience Engine, or on-the-shelf of our platform partners where Experian Audiences are ready to activate. Built on trusted identity data and enhanced with partner insights, it’s where accuracy meets accessibility, helping brands power campaigns with confidence across every channel. Latest posts