
Originally appeared on MarTech Series
Marketing’s understanding of identity has evolved rapidly over the past decade, much like the shifting media landscape itself. From the early days of basic direct mail targeting to today’s complex omnichannel environment, identity has become both more powerful and more fragmented. Each era has brought new tools, challenges, and opportunities, shaping how brands interact with their customers.
We’ve moved from traditional media like mail, newspapers, and linear/network TV, to cable TV, the internet, mobile devices, and apps. Now, multiple streaming platforms dominate, creating a far more complex media landscape. As a result, understanding the customer journey and reaching consumers across these various touchpoints has become increasingly difficult. Managing frequency and ensuring effective communication across channels is now more challenging than ever.
This development has led to a fragmented view of the consumer, making it harder for marketers to ensure that they are reaching the right audience at the right time while also avoiding oversaturation. Marketers must now navigate a fragmented customer journey across multiple channels, each with its own identity signals, to stitch together a cohesive view of the customer.
Let’s break down this evolution, era by era, to understand how identity has progressed—and where it’s headed.
2010-2015: The rise of digital identity – Cookies and MAIDs
Between 2010 and 2015, the digital era fundamentally changed how marketers approached identity. Mobile usage surged during this time, and programmatic advertising emerged as the dominant method for reaching consumers across the internet.
The introduction of cookies and mobile advertising IDs (MAIDs) became the foundation for tracking users across the web and mobile apps. With these identifiers, marketers gained new capabilities to deliver targeted, personalized messages and drive efficiency through programmatic advertising.
This era gave birth to powerful tools for targeting. Marketers could now follow users’ digital footprints, regardless of whether they were browsing on desktop or mobile. This leap in precision allowed brands to optimize spend and performance at scale, but it came with its limitations. Identity was still tied to specific browsers or devices, leaving gaps when users switched platforms. The fragmentation across different devices and the reliance on cookies and MAIDs meant that a seamless, unified view of the customer was still out of reach.
2015-2020: The age of walled gardens
From 2015 to 2020, the identity landscape grew more complex with the rise of walled gardens. Platforms like Facebook, Google, and Amazon created closed ecosystems of first-party data, offering rich, self-declared insights about consumers. These platforms built massive advertising businesses on the strength of their user data, giving marketers unprecedented targeting precision within their environments.
However, the rise of walled gardens also marked the start of new challenges. While these platforms provided detailed identity solutions within their walls, they didn’t communicate with one another. Marketers could target users with pinpoint accuracy inside Facebook or Google, but they couldn’t connect those identities across different ecosystems. This siloed approach to identity left marketers with an incomplete picture of the customer journey, and brands struggled to piece together a cohesive understanding of their audience across platforms.
The promise of detailed targeting was tempered by the fragmentation of the landscape. Marketers were dealing with disparate identity solutions, making it difficult to track users as they moved between these closed environments and the open web.
2020-2025: The multi-ID landscape – CTV, retail media, signal loss, and privacy
By 2020, the identity landscape had splintered further, with the rise of connected TV (CTV) and retail media adding even more complexity to the mix. Consumers now engaged with brands across an increasing number of channels—CTV, mobile, desktop, and even in-store—and each of these channels had its own identifiers and systems for tracking.
Simultaneously, privacy regulations are tightening the rules around data collection and usage. This, coupled with the planned deprecation of third-party cookies and MAIDs has thrown marketers into a state of flux. The tools they had relied on for years were disappearing, and new solutions had yet to fully emerge. The multi-ID landscape was born, where brands had to navigate multiple identity systems across different platforms, devices, and environments.
Retail media networks became another significant player in the identity game. As large retailers like Amazon and Walmart built their own advertising ecosystems, they added yet another layer of first-party data to the mix. While these platforms offer robust insights into consumer behavior, they also operate within their own walled gardens, further fragmenting the identity landscape.
With cookies and MAIDs being phased out, the industry began to experiment with alternatives like first-party data, contextual targeting, and new universal identity solutions. The challenge and opportunity for marketers lies in unifying these fragmented identity signals to create a consistent and actionable view of the customer.
2025: The omnichannel imperative
Looking ahead to 2025 and beyond, the identity landscape will continue to evolve, but the focus remains the same: activating and measuring across an increasingly fragmented and complex media environment. Consumers now expect seamless, personalized experiences across every channel—from CTV to digital to mobile—and marketers need to keep up.
The future of identity lies in interoperability, scale, and availability. Marketers need solutions that can connect the dots across different platforms and devices, allowing them to follow their customers through every stage of the journey. Identity must be actionable in real-time, allowing for personalization and relevance across every touchpoint, so that media can be measurable and attributable.
Brands that succeed in 2025 and beyond will be those that invest in scalable, omnichannel identity solutions. They’ll need to embrace privacy-friendly approaches like first-party data, while also ensuring their systems can adapt to an ever-changing landscape.
Adapting to the future of identity
The evolution of identity has been marked by increasing complexity, but also by growing opportunity. As marketers adapt to a world without third-party cookies and MAIDs, the need for unified identity solutions has never been more urgent. Brands that can navigate the multi-ID landscape will unlock new levels of efficiency and personalization, while those that fail to adapt risk falling behind.
The path forward is clear: invest in identity solutions that bridge the gaps between devices, platforms, and channels, providing a full view of the customer. The future of marketing belongs to those who can manage identity in a fragmented world—and those who can’t will struggle to stay relevant.
Contact us
Latest posts

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. The ability to source high-quality third-party data is core to their business, not an afterthought. 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. Why the future of third-party data depends on accountability The third-party data industry has already crossed the threshold from expansion to accountability. The companies leading this era have established their credibility through governance and proof. The future belongs to providers that: Build with regulatory foresight Maintain rigorous quality assurance Prioritize partnership over profit The Wild West days are long gone. The third-party data ecosystem is now defined by stability, transparency, and shared responsibility. Partner with Experian for data you can trust and results you can prove When accuracy and accountability define success, you need a partner built on both. 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. How does Experian ensure compliance with evolving privacy regulations? Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. 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. 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. What should marketers look for in a data partner? Marketers should look for transparency, longevity, and evidence of compliance when looking for a data partner. The best partners can clearly explain how their data is sourced, validated, and maintained. Read Experian\’s guide on how you can swipe right on the perfect data partner here. Latest posts

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 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