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: 1. Accurate Verified and anchored in real human identity. 2. Fresh Continuously updated to reflect today’s consumers. 3. Consented Collected and governed transparently. 4. Interoperable Easily integrated across platforms through a secure, signal-agnostic identity spine, enabling seamless data activation. This is the data AI can trust and the data that keeps marketing relevant, predictive, and privacy-first. Listen to InfoSum's Identity Architect's podcast for more on AI, outcomes, and curation 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. 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 Outdated data can’t predict tomorrow’s behavior.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. 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. 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 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 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

2024 marked a significant year. AI became integral to our workflows, commerce and retail media networks soared, and Google did not deprecate cookies. Amidst these changes, ID bridging emerged as a hot topic, raising questions around identity reliability and transparency, which necessitated industry-wide standards. We believe the latest IAB OpenRTB specifications, produced in conjunction with supply and demand-side partners, set up the advertising industry for more transparent and effective practices. So, what exactly is ID bridging? As signals, like third-party cookies, fade, ID bridging emerged as a way for the supply-side to offer addressability to the demand-side. ID bridging is the supply-side practice of connecting the dots between available signals, that were generated in a way that is not the expected default behavior, to understand a user’s identity and communicate it to prospective buyers. It enables the supply-side to extend user identification beyond the scope of one browser or device. Imagine you visit a popular sports website on your laptop using Chrome. Later, you use the same device to visit the same sports website, but this time, on Safari. By using identity resolution tools, a supply-side partner can infer that both visits are likely from the same user and communicate with them as such. ID bridging is not inherently a bad thing. However, the practice has sparked debate, as buyers want full transparency into the use of a deterministic identifier versus an inferred one. This complicates measurement and frequency capping for the demand-side. Before OpenRTB 2.6, ID bridging led to misattribution as the demand-side could not attribute ad exposures, which had been served to a bridged ID, to a conversion, which had an ID different from the ad exposure. OpenRTB 2.6 sets us up for a more transparent future In 2010, the IAB, along with supply and demand-side partners, formed a consortium known as the Real-Time Bidding Project for companies interested in an open protocol for the automated trading of digital media. The OpenRTB specifications they produced became that protocol, adapting with the evolution of the industry. The latest evolution, OpenRTB 2.6, sets out standards that strive to ensure transparency in real-time bidding, mandating how the supply-side should use certain fields to more transparently provide data when inferring users’ identities. What's new in OpenRTB 2.6? Here are the technical specifications for the industry to be more transparent when inferring users’ identities: Primary ID field: This existing field now can only contain the “buyeruid,” an identifier mutually recognized and agreed upon by both buyer and seller for a given environment. For web environments, the default is a cookie ID, while for app activity, it is a mobile advertising ID (MAID), passed directly from an application downloaded on a device. This approach ensures demand-side partners understand the ID’s source.  Enhanced identifier (EID) field: The EID field, designated for alternative IDs, now accommodates all other IDs. The EID field now has additional parameters that provide buyers transparency into how the ID was created and sourced, which you can see in the visual below:  Using the above framework, a publisher who wants to send a cross-environment identifier that likely belongs to the same user would declare the ID as “mm=5,” while listing the potential third-party identity resolution partner under the “matcher” field, which the visual below depicts. This additional metadata gives the demand-side the insights they need to evaluate the reliability of each ID. "These updates to OpenRTB add essential clarity about where user and device IDs come from, helping buyers see exactly how an ID was created and who put it into the bidstream. It’s a big step toward greater transparency and trust in the ecosystem. We’re excited to see companies already adopting these updates and can’t wait to see the industry fully embrace them by 2025."Hillary Slattery, Sr. Director, Programmatic, Product Management, IAB Tech Lab Experian will continue supporting transparency As authenticated signals decrease due to cookie deprecation and other consumer privacy measures, we will continue to see a rise in inferred identifiers. Experian’s industry-leading Digital Graph has long supported both authenticated and inferred identifiers, providing the ecosystem with connections that are accurate, scalable, and addressable. Experian will continue to support the industry with its identity resolution products and is supportive of the IAB’s efforts to bring transparency to the industry around the usage of identity signals. Supply and demand-side benefits of adopting the new parameters in OpenRTB 2.6 Partner collaboration: Clarity between what can be in the Primary ID field versus the EID field provides clear standards and transparency between buyers and sellers. Identity resolution: The supply side has an industry-approved way to bring in inferred IDs while the demand side can evaluate these IDs, expanding addressability. Reducing risk: With accurate metadata available in the EID field, demand-side partners can evaluate who is doing the match and make informed decisions on whether they want to act on that ID. Next steps for the supply and demand-sides to consider For supply-side and demand-side partners looking to utilize OpenRTB 2.6 to its full potential, here are some recommended steps: For the supply-side: Follow IAB Specs and provide feedback: Ensure you understand and are following transparent practices. Ask questions on how to correctly implement the specifications. Vet identity partners: Choose partners who deliver the most trusted and accurate identifiers in the market. Be proactive: Have conversations with your partners to discuss how you plan to follow the latest specs, which identity partners you work with, and explain how you plan to provide additional signals to help buyers make better decisions. We are beginning to see SSPs adopt this new protocol, including Sonobi and Yieldmo.  “The OpenRTB 2.6 specifications are a critical step forward in ensuring transparency and trust in programmatic advertising. By aligning with these standards, we empower our partners with the tools needed to navigate a cookieless future and drive measurable results.” Michael Connolly, CEO, Sonobi These additions to the OpenRTB protocol further imbue bidding transactions with transparency which will foster greater trust between partners. Moreover, the data now available is not only actionable, but auditable should a problem arise. Buyers can choose, or not, to trust an identifier based on the inserter, the provider and the method used to derive the ID. While debates within the IAB Tech Lab were spirited at times, they ultimately drove a collaborative process that shaped a solution designed to work effectively across the ecosystem.”Mark McEachran, SVP of Product Management, Yieldmo For the demand side: Evaluation: Use the EID metadata to assess all the IDs in the EID field, looking closely at the identity vendors’ reliability. Select partners who meet high standards of data clarity and accuracy. Collaboration: Establish open communication with supply-side partners and tech partners to ensure they follow the best practices in line with OpenRTB 2.6 guidelines and that there’s a shared understanding of the mutually agreed upon identifiers. Provide feedback: As OpenRTB 2.6 adoption grows, consistent feedback from demand-side partners will help the IAB refine these standards. Moving forward with reliable data and data transparency As the AdTech industry moves toward a cookieless reality, OpenRTB 2.6 signifies a substantial step toward a sustainable, transparent programmatic ecosystem. With proactive adoption by supply- and demand-side partners, the future of programmatic advertising will be driven by trust and transparency. Experian, our partners, and our clients know the benefits of our Digital Graph and its support of both authenticated and inferred signals. We believe that if the supply-side abides by the OpenRTB 2.6 specifications and the demand-side uses and analyzes this data, the programmatic exchange will operate more fairly and deliver more reach. Contact us Latest posts

Originally appeared on MediaPost As the digital ecosystem becomes more complex, managing multiple identifiers for consumers has emerged as a significant challenge. From cookies and IP addresses to mobile IDs and universal IDs, marketers and platforms face increasing difficulty in maintaining a unified view of their consumers. Without a coherent identity strategy, campaigns can suffer from poor targeting, limited personalization, and flawed attribution. Experian understands these challenges and offers solutions to help our partners navigate the complexities of a multi-ID landscape. By utilizing both digital and offline data, we provide the tools to unify fragmented identifiers and maintain a persistent view of consumers. As a result, marketers and platforms get rich insights, accurate cross-device targeting, improved addressability, and measurable advertising. The shifting identity landscape For years, the industry has relied on cookies to identify consumers across devices and platforms. However, with ongoing signal loss, including the uncertainty around cookies, and the evolution of privacy regulations, the digital identity landscape has grown more complicated. As consumers hop from one device to another, they are now represented by multiple signals, each tied to a different aspect of their digital behavior. While this shift brings complexity, it also opens the door for innovation. Marketers and ad platforms now have the opportunity to rethink their identity strategies and adopt more flexible approaches that are not reliant on a single identifier. This is where Experian comes in. Connecting the dots: A holistic view of the customer journey Our identity solutions are designed to help manage today’s multi-ID ecosystem by connecting digital and offline identifiers to a single customer profile. This creates a unified view of the consumer, and when combined with our understanding of customer behavior (e.g. demo, interests, shopping patterns) marketers and platforms get both insights about their customers and the addressability to reach them across channels. Four examples of what you can do with a strong identity foundation If an advertiser wants to make its first-party data more addressable, it can utilize our Digital Graph with universal IDs, hashed emails (HEMs), and connected TV (CTV) IDs to extend its reach. A publisher who wants to gain further insights into their audiences and create private marketplaces (PMPs) can achieve this goal with the use of our Digital Graph with hashed emails, universal IDs, mobile ad IDs (MAIDs), CTV IDs, and IPs. The publisher can use this in concert with Marketing Attributes to understand age, gender, household income, buying behavior, and more. The publisher can connect marketing attributes to the Digital Graph via our Living Unit ID (LUID) to understand more about consumers that fall into their segments. A demand-side platform (DSP) who wants to extend first-party and third-party audience reach across all digital devices on their platform will use the Digital Graph with all digital IDs to allow users of their platform to select cross-device extension against first-party and third-party audiences. A retail media network (RMN) can use our Offline and Digital Graphs to connect in-store and online purchases to a household profile—even when purchases are made by different people. The RMN can then reach that household across digital media platforms and accurately attribute the in-store purchase back to digital ad exposure.  Identity as a strategic asset: Today and in the future In our paradoxical world where consumers are represented by multiple identifiers, yet marketers and platforms face signal loss, identity is more than a technical issue—it’s a strategic asset. The ability to unify identity data into a single profile provides marketers with the customer intelligence needed to drive growth and stay competitive. Here’s how we do it: Deep, persistent customer understanding: With roots in offline, deterministic data like names, addresses, and emails, we provide an accurate and persistent view of identity to our customers. This allows you to maintain a consistent and comprehensive understanding of your customers and their marketing attributes over time. Highly accurate and refreshed digital identities: Our signal-agnostic graph is not reliant on any one signal as it includes HEMs, cookies, MAIDs, IPs, Universal IDs, and CTV IDs. Our Digital Graph is updated weekly, ensuring the data is always fresh and addressable. This persistent linkage of individuals and households to their identifiers and devices means your campaigns are always targeting the right people. Connected offline and digital graphs for holistic insights: We connect offline and digital identities by following privacy-first best practices, such as preventing re-identification, to allow insights from the offline world to be used in the online world. This integrated approach, enriched with marketing data, gives you better insights, more addressable advertising, and the ability to engage customers across multiple devices while accurately measuring campaign impact. Transform challenges into opportunities The rise of the multi-ID landscape presents both challenges and opportunities for the advertising industry. We stand as the trusted partner to navigate this complexity, utilizing insights from the offline world to inform decisions in the online world, enabling personalized marketing and accurate attribution, and helping you achieve your current and future goals. Get started today Latest posts

Connected TV (CTV) is a leading platform in digital advertising, combining the precise targeting of digital ads with the broad reach and storytelling power of traditional TV. This creates an immersive experience that offers full-funnel marketing results. As consumer time spent watching CTV has doubled over the past five years and linear TV viewing patterns have shifted, advertisers now see CTV as essential for reaching and engaging audiences.

Experian offers a suite of next-generation tools built on the Experian Digital Graph to help marketers adapt to ongoing signal fragmentation and privacy regulation. These solutions enable brands to maintain behavioral targeting and campaign performance even as traditional signals decrease. Through Experian's integration with Audigent, we now offer early access to Curated Deals, contextually-indexed audiences, and Geo-Indexed Audiences that help advertisers test privacy-first audience activation in a period of accelerating signal fragmentation.  Experian and Audigent offer a data management platform (DMP) that enables publishers to collect, manage, and understand their first-party data, while also accessing third-party data, to better monetize their data assets. At the same time, Experian continues to advance its signal-agnostic Digital Graph, which already covers industry-standard universal IDs, like Unified ID 2.0 (UID2) and ID5, as well as both IPv4 and IPv6, which are becoming more and more prevalent. Together, these updates give marketers a reliable, privacy-forward foundation for audience reach, cross-device targeting, and measurement as signal fragmentation continues to reshape digital advertising. How is Experian's Digital Graph evolving in a multi-signal world? Signal fragmentation is reshaping how marketers reach and measure audiences, so we continue to strengthen the Experian Digital Graph to keep performance steady across channels. Recent updates focus on improving connectivity, accuracy, and durability: More signals to keep reach strong: We added IPv6 and phone-based UID2s to our Digital Graph, building on the hashed email (HEM)-based UID2s we already support. Better AI models for cleaner identity data: We improved our AI clustering and device classification models to sharpen ID resolution. More stable customer profiles: We enhanced stability in our Digital Graph by tying it more closely to our Offline Graph, ensuring more complete customer profiles that last over time. Together, these updates give marketers a more resilient identity foundation and help maintain performance in a market defined by rising signal fragmentation. How is Experian advancing contextual targeting and geo-based targeting with our partners? AWith more signals in market and traditional identifiers becoming less reliable advertisers are returning to tactics that don’t rely on cookies. Contextual targeting and geo-based targeting have both delivered results for years, and are becoming even more important as marketers look for consistent ways to reach audiences without relying on ID-level data. Experian is modernizing these approaches by pairing Experian Marketing Data with contextual and geographic signals to create privacy-first activation paths that hold up as identifiers fade. With our acquisition of Audigent, we’re expanding the ways marketers can activate privacy-forward audiences at scale. Together, these capabilities strengthen how brands reach people with relevant experiences, even as traditional IDs fade:  Contextually- Indexed Audiences: We index Experian’s syndicated audiences against contextual signals inside private marketplace (PMP) deals using Experian’s Digital Graph and Audigent’s Hadron ID. In a 15-day test with a national advertiser, this ID-less approach exceeded click-through rate goals by 25% while matching the scale and delivery of ID-based campaigns. Geo-Indexed Audiences: We also offer Geo-Indexed Audiences that use location-based signals to reach consumers in the right places and moments, providing another durable option when IDs are unavailable or restricted. Evolving toward more intent-rich signals: Looking ahead, we are developing ways to incorporate additional intent indicators, such as content consumption patterns and repeated contextual behaviors, to give marketers stronger cues about where their audiences are in their decision process, all without relying on user-level identifiers. Together, these tactics make contextual and geo-based targeting more measurable, scalable, and privacy-safe, helping marketers keep performance steady as signal fragmentation accelerates. Which alternative IDs does Experian's Digital Graph support? Experian’s signal-agnostic Digital Graph is designed to interoperate across identity frameworks and connect digital identifiers into a single, privacy-compliant system. It now supports alternative IDs such as: UID2s ID5 IDs HEMs Connected TV (CTV) IDs Our Digital Graph is rebuilt weekly to maintain high accuracy and addressability across campaigns. These capabilities ensure marketers can continue cross-device activation and measurement as legacy signals decline. “Experian is a valued partner in Nexxen’s unified identity graph powering the Nexxen data platforms, which bring us the ability to seamlessly onboard client data, activate campaigns, and measure performance while maximizing biddable opportunities for our advertisers. They help ensure our clients can continue reaching audiences at scale and successfully execute campaigns.”Chance Johnson, Chief Commercial Officer What's next for Experian's identity and connectivity roadmap? As digital signals change and CTV viewership grows, we continue to expand the identifiers supported within the Experian Digital Graph. Recent additions such as IPv6 and phone-based UID2s, alongside existing IPv4 and email-based IDs, help marketers and platforms understand the full customer journey across screens and households within a privacy-first framework. We are committed to maintaining and increasing connectivity in the digital world, ensuring that clients can reach their audiences even as familiar signals decline. A core part of that commitment is strengthening the overlap between our Offline and Digital Graphs. This work improves cross-channel consistency and gives marketers more reliable links between individuals, households, and devices. As we keep investing in identity resilience, clients can expect ongoing innovation that supports addressability and performance despite evolving privacy constraints. Start exploring privacy-first audience targeting through Experian's data marketplace How can marketers maintain addressability at scale today? Experian’s connected toolkit of signal-agnostic advertising solutions empowers brands to continue reaching audiences with confidence: Identity resolution through Experian’s Digital Graph Curation via Audigent Cross-device measurement built for privacy compliance Universal ID interoperability across platforms As the industry adjusts to signal fragmentation, Experian provides the scale, trust, and connectivity required to sustain effective targeting. A resilient path forward for addressable advertising As the AdTech industry continues to evolve, Experian’s Digital Graph continues to power interoperability, scale, and privacy-safe measurement. With data ranked #1 in accuracy by Truthset, collaborations across the AdTech ecosystem, and ongoing support for universal IDs, Experian gives marketers a reliable path to addressable, measurable, and privacy-first advertising. Connect with our team About the author Budi Tanzi, VP of Product and Solution Engineering, Experian Marketing Services 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. FAQs How does Experian's Digital Graph help marketers prepare amidst signal fragmentation? Experian’s Digital Graph enables consistent audience targeting and measurement across browsers and devices using privacy-compliant identifiers. It connects verified digital data, giving advertisers continuity as traditional IDs become less reliable.Experian’s Digital Graph supports consistent audience targeting and measurement across browsers and devices using privacy-compliant identifiers. By connecting verified digital data, the Digital Graph gives marketers continuity as signals such as cookies, device IDs, and IP-based identifiers become less reliable. Recent updates, including IPv6, phone-based UID2s, and improved AI clustering, help you maintain reach and accuracy even as digital signals shift. What partners support Experian’s signal fragmentation strategy? Experian works with a variety of partners to source digital IDs. We work with The Trade Desk and ID5 to incorporate their universal IDs into our Digital Graph. Additionally, Audigent, now a part of Experian, offers Curated Deals, which are a non-cookie dependent way to provide reach and relevance.  Does Experian’s Digital Graph comply with privacy standards? Yes. Experian’s identity and data solutions align with IAB Data Privacy Standards and regulations such as the California Consumer Privacy Act (CCPA), ensuring transparent and compliant data use. What future plans does Experian have for the Digital Graph? Our current focus is to increase the overlap between our Offline and Digital Graphs, enabling more cross-channel addressability for our clients. We also continue expanding supported identifiers and improving our AI models to maintain performance as signal fragmentation grows. How can I get started testing Experian’s signal-agnostic solutions? You can reach out directly to explore privacy-first activation options, including contextual, geo-indexed, curated deals, and ID-based strategies supported by the Experian Digital Graph. Latest posts