At A Glance
AI learns what your data teaches in 2025, "good data" in AI means accurate, current, consented, and easy to connect, or your models lose relevance and your investments underperform. Experian is leading this next era of responsible data where trust, transparency, and innovation come together to make marketing more human, not less.What makes data “good” in the age of AI?
In AI-driven marketing, data quality now defines success. “Good data” in AI isn’t about volume; it’s about the balance of accuracy, freshness, consent, and interoperability. As algorithms guide decisions, they must learn from data that’s both accurate and ethical.
At Experian, we believe good data must meet four conditions:
This is the data AI can trust and the data that keeps marketing relevant, predictive, and privacy-first.
Why does data accuracy matter more than ever?
AI models are only as intelligent as their inputs. Incomplete or inconsistent data leads to bad predictions and wasted spend. As the industry moves toward agentic advertising, where autonomous systems handle campaign buying and optimization, data accuracy becomes even more critical. If your ad server or audience data is flawed, these new AI agents will simply automate bad decisions faster.
Experian applies rigorous quality filters and conflict resolution rules to ensure our data is both deterministic and accurate. Deterministic signals alone don’t guarantee accuracy; they must be verified, deduplicated, and contextualized. Our identity resolution process anchors every attribute to real people, giving brands and platforms the confidence that every insight stems from truth, not noise.

Our data is ranked #1 in accuracy by Truthset, giving our clients confidence that every decision they make is backed by the industry’s most reliable insights.
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.
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Outdated data can’t predict tomorrow’s behavior.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.
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. Our signal-agnostic identity spine allows data to move securely between platforms (connected TV, retail media networks, and demand-side platforms) without losing context or compliance.

Interoperability isn’t just about moving data between systems; it’s about connecting insights across them. When signals connect across environments, AI gains a more complete view of the customer journey revealing true behavior patterns, intent signals, and cross-channel impact that would otherwise remain hidden.
This unified perspective allows AI to connect insights in real time, improving predictions, performance, and personalization while protecting privacy.
Where do AI and human oversight meet?
AI can make marketing more predictive, but people make it meaningful. At Experian, our technology brings identity, insight, and generative intelligence together so brands, agencies, and platforms can reach the right people with relevance, respect, and simplicity.

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.
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.
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:
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 ad-tech 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.
“Good” data in AI FAQs
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.
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.
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.
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.
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

Over the last few months, Experian has released new syndicated audiences to most major platforms supporting retail and travel. In this blog post, we’ll highlight some of these new audiences and how they can be used with other data from Experian to build the perfect audience to reach your customers and prospects. What separates Experian's syndicated audiences Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, programmatic advertising platforms, and directly within Audigent for activation within private marketplaces (PMPs). Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes. Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent for activation in PMPs and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk. Household Expenditure audiences We’ve created new predictive audiences to help retailers reach consumers across 35 categories likely to spend within that category. A few categories include Apparel, DIY, Health, and more. With the launch of these new audiences, we will retire our existing Household Consumer Expenditure, Online and Retail category audiences in the November Digital Master update. Who these audiences are for Our Household Expenditure audiences use data from multiple sources, providing brands with highly accurate purchase predictions and data that scales for digital execution. Household Expenditure audiences are an excellent solution for brands with new product lines or where targeting based on historical purchases lack signal brands seek. Building data from multiple data sources helps ensure high performance and accuracy and can illuminate trends in consumer shopping patterns. These trends can be used to help predict future shopping behaviors. How to refine our Household Expenditure audiences To refine your audience, you can combine this data with Experian’s demographic and household expenditure audiences to ensure you are reaching consumers. For example, suppose you’re an apparel brand launching a new line aimed toward women over the age of 40. In that case, you can use Experian’s demographic data to reach those women and layer in our household expenditure purchase predictor segment for women's apparel to reach their new target audience. Mobile Location audiences We’ve expanded our location database to include more locations and points of interest. With this new data, we could strengthen our existing mobile location audiences to broaden the reach, improve accuracy, and increase performance. We’ve created 11 new mobile location audiences with our new dataset that supports the retail and travel verticals. These new audiences include new shopping behaviors, including high-income and high-end shoppers and travel and entertainment behaviors, including visiting sporting arenas like MLB, NBA, NFL, and university stadiums. Who these audiences are for These audiences are for brands that want to reach consumers based on their location behaviors. Often valid for retail, travel, and entertainment brands, Mobile Location audiences provide brands with highly accurate data that shows previous intent and interest in critical locations. How to refine our Mobile Location audiences To refine your audience, you can combine your Mobile Location audience with Lifestyle and Interest data. For example, if you are creating an advertising campaign for a hotel near a university stadium for the largest game in the season, you could combine university stadium visitors with sports enthusiasts and in-market for travel to find consumers most likely to be interested in your campaign and staying at the hotel. Purchase-Based Transaction audiences For use cases where predictive audiences aren’t the best fit to reach the right consumer, such as targeting consumer’s historical purchases, we’ve created new purchase-based transaction audiences that utilize opt-in consumer transaction data across 29 retail categories, including apparel, home, lifestyle, health, food and beverage, and more. Who these audiences are for These audiences are a perfect fit for brands trying to reach consumers based on previous purchases. These audiences can be broken out by their spending patterns – frequency of purchase and high spenders – and their response to advertising, including direct mail, email, inserts, and digital. How to refine our Purchase-Based Transaction audiences Combine these new audiences with Mosaic to fine-tune your audience based on their purchasing and lifestyle patterns. Suppose you are a brand with a new line of home décor products launching and will utilize influencers to endorse your product line. In that case, you can use Experian’s purchase-based transaction audiences for high spenders in home décor and layer our Mosaic audience Influenced by Influencers to find consumers who are most likely to purchase and trust an influencer. We can help you discover and activate your perfect audience Our audiences are available in most major data and execution platforms. Visit our partner page for more information. Don’t see our audiences on your platform of choice? We can help you build and activate an Experian audience on the platform of your choice. Contact us Latest posts

The AdTech industry is buzzing with discussions about cookie deprecation and effective strategies to tackle it. One of the commonly suggested solutions is the utilization of clean rooms alongside responsibly sourced first-party data. Above all else, the industry recognizes the importance of respecting consumer data and complying with all privacy laws. Additionally, the industry acknowledges the need for a change in our historical practices. This shift benefits everyone involved, as consumer data is more secure than ever. Tremendous investments have been made to ensure the utmost security of consumer information. Clean rooms are one of the tools that enable companies to use data securely, ensuring the content that you see is as relevant as possible. Two ways the AdTech industry is addressing cookie deprecation The days of sending data directly to partners for usage or for using only third-party data for marketing efforts are gone. Now, the emphasis is on responsibly collecting first-party data and using clean rooms to enrich first-party data to enhance marketing efforts. First-party data The industry is starting to lean into first-party data gained through transparent means. This valuable information provides organizations with deeper insights into their customers, allowing for more personalized and effective interactions. By embracing the power of first-party data, either on its own or enriched via partner collaboration, you can cultivate stronger relationships, build trust, and deliver tailored experiences that resonate with your customers on a deeper level. Clean rooms Many data lakes and warehouses offer this service, ensuring their clients can not only store their data with them but can connect it with other partners in a secure environment and extract more information through the combined data sets versus their data on its own. Brands and their partners recognize that they need to work together, and a clean room provides a secure environment to share their first-party data without exposing their sensitive data to their partner. So, while we're losing third-party cookies, brands and partners can still get value from first-party data by using a clean room to generate audience insights, segmentation strategies, personalized experiences and offers, media plans, and measurement and attribution. Three ways data clean rooms can improve Data clean rooms are a great way to facilitate data collaboration while ensuring sensitive data is not exposed. Data clean rooms are not yet easy to use nor are they inexpensive. They require investment, both financially and resource allocation-wise, and you are not guaranteed to yield great match results. Let’s dive into three areas for data clean room improvement. High cost According to the IAB's State of Data 2023, nearly two-thirds of data clean room users spent at least $200K on the technology in 2022. In addition, one-third of data clean room users expect the price of data clean rooms to rise in 2023. The high cost of this solution can make it inaccessible to smaller companies in the advertising space. Resource intensive Nearly half of the companies using data clean rooms have a team of six or more dedicated to the technology, according to the IAB’s State of Data 2023, while nearly a third of companies using data clean rooms have 11 or more employees focused on the technology. Data clean rooms are not turnkey solutions. Inefficient matching Even if companies are using clean rooms does not mean that they are automatically going to achieve great success. Identity fragmentation, data hygiene, and differing identifiers can suppress client match rates in clean rooms, leading to significant investment and a lackluster output. How to get the most return on your clean room investment The finish line for data collaboration in clean rooms is not just having a relationship with a clean room. Instead, you should incorporate an identity resolution solution in your clean room. By adding an identity solution to your clean room, you can: Resolve and match all your identity data, regardless of the identity data that you or your partner have, giving you a larger data foundation to analyze. Generate more valuable insights and information, leading to a better experience for your customers. Join data sets to create smarter activation and targeting strategies and produce more holistic measurement. Experian can help you get started with identity resolution and data clean rooms If you are investing in data clean rooms, that means you are committed to the best in data practices. Experian recommends going the extra step and that you also invest in finding an identity resolution solution. By doing this, you can see better match rates. Experian offers this capability and has existing relationships with three clean room partners, Amazon Web Services, InfoSum, and Snowflake. In addition to collaborating in clean rooms, we offer collaboration in two other secure environments. Contact us today to discuss how we enable identity resolution in clean rooms or to chat about our other collaboration capabilities. Get in touch Latest posts

Ongoing signal loss is driving marketers, agencies, and platforms to turn to supply-side advertising. By using first-party data from publishers and platforms, supply-side advertising has the potential to deliver high-quality audience and context for more effective ad targeting. The supply-side refers to the publishers and platforms that sell advertising inventory. These companies have access to first-party data about their users, which can be used to target ads more effectively. By tapping into supply-side advertising, you can overcome the challenges of signal loss and target ads more effectively. To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from Audigent, Captify, Newsweek, Pubmatic, Truthset, and Experian. In this blog post, we'll explore how partnerships between supply-side channels and publishers are working to enhance advertising opportunities while balancing the need for transparency and control in programmatic ad buying. Shift toward supply-side advertising Traditionally, the demand-side dominated the programmatic media buying chain due to an abundance of supply. However, with the emergence of finite data and its interpretation, collaboration between supply-side technology companies and publishers is required to redefine these economics. It's no longer sufficient for the demand-side to blindly negotiate prices based on limited knowledge. Marketers can still define their target audience, but effective communication is key. This presents an opportunity for premium journalistic outlets to guide the industry's understanding of how data from the supply-side impacts media buying economics in the future. "Supply-side technology partnerships with publishers are now in a position to shape the economics of programmatic media buying as there is a finite amount of data. It’s crucial for supply-side technology companies to collaborate with publishers to shape these new economics. This presents an opportunity for premium journalistic outlets to provide guidance on how data from the supply-side can affect the future of media buying." matthew papa, svp, business & corporate development, captify Democratizing data from the supply-side Cookies haven't brought significant benefits to premium publishers. They mainly serve to retarget users from sites like The Wall Street Journal to advertising sites. This approach primarily serves the purpose of generating revenue. The elimination of third-party cookies presents an opportunity for premium publishers to shift this dynamic. By using their knowledge of first-party audiences, and using identifiers like Experian's LUID, publishers can own and understand their audience data, which can then be modeled. Here’s how publishers can win Establishing a connection with consumers and emphasizing the value exchange is essential to building trust. Determining what incentives and benefits consumers find meaningful will be crucial in gaining their opt-in. With consumers The Apple tracking transparency initiative, specifically the deprecation of IDFA signals, had significant implications for mobile app developers. Overnight, opt-in rates plummeted, causing a drastic decline in iOS ad monetization. To combat this, developers focused on demonstrating the value exchange to consumers—better ad experiences and personalized content. By articulating the benefits over a couple of years, opt-in rates increased from 10-15% to 30-40%. The key takeaway is the need to effectively communicate the value exchange to consumers. With partners Trust plays a crucial role in planning your first-party data strategy. Publishers, advertisers, and data partners highly value their proprietary data. However, there are concerns about how it's used, mishandled, or leaked in the ecosystem. Building trust between partners is essential. It's important to work with trustworthy partners who are agnostic, committed to innovative solutions, and globally oriented. These partners can help navigate the complexities of laws and regulations. Choosing the right partners is crucial in a world where first-party data is a key asset. "Power is shifting toward brands that have strong relationships with customers and possess first-party data. As the ownership of customer data becomes more important, it is crucial to establish a first-party data strategy to better serve customers and adapt to changing market dynamics."chip russo, president, truthset Balance probabilistic and deterministic data Focus on building trust with consumers and collaborating with reliable companies to share data. However, it's important to remember that achieving a 100% opt-in rate is unlikely. The cookie, which has become omnipresent, requires us to shift our strategic thinking. We need to consider both deterministic and probabilistic approaches instead of viewing them as mutually exclusive. The landscape will be fragmented, with some consumers opting in and others not. "Probabilistic and predictive audience data holds immense potential. With the power of AI, we can expect enhanced performance and efficacy in media campaigns. At Audigent, we firmly believe that this data will outperform deterministic data, making it an integral part of our strategy." drew stein, ceo, audigent Premium content Trust plays a crucial role in leading to premium content. By placing trust in the best media brands, data, and technology partners, we can expect to see improvements in media, journalism, and advertising. This shift may have a direct impact on the long tail of free natural resources, making it more challenging for them to thrive. However, this change is ultimately beneficial since it promotes higher-quality media experiences overall. "The homepage surface is making a comeback in the publishing industry, proving its value in establishing a direct connection with readers. While we acknowledge the importance of technology partnerships for addressability and identity, our core competency as a publisher remains outstanding journalism that captures and engages great audiences." kevin gentzel, cco, newsweek Watch our Cannes panel for more on supply-side advertising We hosted a panel in Cannes that covered supply-side advertising. Check out the full recording below to hear what leaders from Audigent, Captify, Newsweek, Pubmatic, Truthset, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 Exploring the opportunities in streaming TV advertising The future of identity in cookieless advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Contact us today Latest posts







