
The cookieless future is here, and it’s time to start thinking about how you will adapt your strategies to this new reality. In a cookieless world, you will need to find new ways to identify and track users across devices. This will require reliance on first-party data, contextual advertising, and alternative identifiers that respect user privacy.
To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian.

In this blog post, we’ll explore the future of identity in cookieless advertising. We’ll discuss the challenges and opportunities that this new era presents, and we’ll offer our tips for how to stay ahead of the curve.
How cookieless advertising is evolving
Programmatic advertising is experiencing multiple changes. Let’s dive into three key things you should know.
Cookie deprecation
One significant change is cookie deprecation, which has implications for tracking and targeting. Additionally, understanding the concept of Return on Advertising Spend (ROAS) is becoming increasingly crucial.
The demand and supply-side are coming closer together
Demand-side platforms (DSPs) and supply-side platforms (SSPs) have traditionally been seen as two separate entities. DSPs are used by advertisers to buy ad space, while SSPs are used by publishers to sell ad space. However, in recent years, there has been a trend toward the two sides coming closer together.
This is due to three key factors:
The rise of header bidding
Header bidding is a process where publishers sell their ad space to multiple buyers in a single auction. This allows publishers to get the best possible price for their ad space, and it also allows advertisers to target their ads more effectively.
Cookie deprecation
As third-party cookies are phased out, advertisers need to find new ways to track users, and they are turning to SSPs for help. SSPs can provide advertisers with data about users, such as their demographics and interests. This data can be used to target ads more effectively.
The increasing importance of data
Advertisers are increasingly looking for ways to target their ads more effectively, and they need data to do this. SSPs have access to a wealth of user data, and they’re willing to share this data with advertisers. This is helping to bridge the gap between the two sides.
The trend toward the demand-side and supply-side coming closer together is good news for advertisers and publishers. It means that they can work together to deliver more relevant ads to their users.
Measuring and tracking diverse types of media
The media measurement landscape is rapidly evolving to accommodate new types of media, such as digital out-of-home (DOOH). With ad inventory expanding comes the challenge of establishing identities and connecting them with what advertisers and agencies want to track.
Measurement providers are now being asked to accurately capture instances when individuals are exposed to advertisements at a bus stop in New York City, for example, and tracking their journey and purchase decisions, such as buying a Pepsi.
To navigate cookieless advertising and measurement, we must prioritize building a strong foundational identity framework.
What you should focus on in a cookieless advertising era
In a cookieless advertising era, you will need to focus on two key things: frequency capping and authentic identity.
Frequency capping
Frequency capping is a practice of limiting the number of times an ad is shown to a user. This is important in cookieless advertising because it helps to prevent users from being bombarded with ads. It also helps to ensure that ads are more effective, as users are less likely to ignore or click on ads that they have seen too many times.
Frequency capping is often overhyped and yet overlooked. Instead of solely focusing on frequency, consider approaching it from an identity perspective. One solution could be to achieve a perfect balance between reaching a wider audience and avoiding excessive repetition. By increasing reach in every programmatic buy, you naturally mitigate frequency control concerns.
Authentic identity
The need for authentic identities in a digital and programmatic ecosystem is undeniable. While we explore ways to connect cookies, mobile ads, and other elements, it’s crucial to remember who we are as real individuals. By using anonymized personal identifying information (PII) as a foundation, we can derive insights about households and individuals and set effective frequency caps across different channels.
Don’t solely focus on devices and behaviors in your cookieless advertising strategy and remember the true value of people and their identities.
What’s next for cookieless advertising?
The deprecation of third-party cookies is a major challenge for the digital advertising industry. Advertisers will need to find new ways to track users and target their ads.
Here are three specific trends that we can expect to see in cookieless advertising.
First-party data is moving in-house
Many major media companies, equipped with valuable identifier and first-party data, are choosing to bring it in-house. They are focused on using their data internally rather than sharing it externally.
“Many larger media companies are opting to bring their identifier and first-party data in-house, creating more walled gardens. It seems that companies are prioritizing data control within their own walls instead of sharing it externally.”
laura manning, svp, measurement, cint
Fragmentation will continue
The number of identifiers used to track people online is growing rapidly. In an average household, over a 60-day period, there are 22 different identifiers present. This number is only going to increase as we move away from cookies and toward other identifiers.
This fragmentation makes it difficult to track people accurately and deliver targeted advertising. This means that we need new identity solutions that can help make sense of these new identifiers and provide a more accurate view of people.
A portfolio of solutions will address signal loss
Advertisers are taking a variety of approaches to cookieless advertising. A few of the solutions include:
- Working with alternative IDs.This refers to using alternative identifiers to cookies, such as mobile device IDs or email addresses. These identifiers can be used to track people across different websites and devices, even without cookies.
- Working with data index at a geo level. This refers to using data from a third-party provider to get a better understanding of people’s location. This information can be used to target ads more effectively.
- Working with publisher first-party data that’s been aggregated to a cohort level. This refers to using data that is collected directly from publishers, such as website traffic data or purchase history. This data can be used to create more personalized ads.
- Working with contextual solutions. This refers to using contextual data, such as the content of a website or the weather, to target ads. This can help to ensure that ads are relevant to the user’s interests.
“Cookie deprecation is often exaggerated, and alternate solutions are already emerging. As data moves closer to publishers and first-party data gains prominence, the industry will adapt to the changes.”
mark walker, ceo, direct digital holdings
There is no one-size-fits-all solution for cookies, and you will need to be flexible and adopt a variety of different approaches.
How will these solutions work together?
You can take a waterfall approach to cookieless advertising. A waterfall approach is a process where advertisers bid on ad impressions in sequential order. The first advertiser to meet the minimum bid price wins the impression.
In the context of cookieless advertising, a waterfall approach can be used to prioritize different targeting signals. For example, you might start by bidding on impressions that have a Ramp ID, then move on to impressions that have a geo-contextual signal, and finally bid on impressions that have no signal at all.
This is a flexible approach that can be adapted to different needs and budgets.
Watch our Cannes panel for more on cookieless advertising

We hosted a panel in Cannes that covered the future of identity in cookieless advertising. Check out the full recording below to hear what leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian had to say.
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
- Maximize ad targeting with supply-side advertising
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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. Third-party data 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

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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. 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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

Artificial intelligence (AI) is becoming a bigger part of modern advertising, changing how brands connect with people. At Experian, we believe this technology should make marketing more human, not less. We use AI to help marketers understand consumer behavior, respect privacy, and deliver messages that matter. As part of our latest Cannes Content Studio series, we spoke with leaders from AdRoll, MiQ, OpenX, Optable, PMG, PubMatic, and Yieldmo. Their insights show a clear path forward; one where technology supports human strategy to create more meaningful connections. 1. How does AI help you see audiences more clearly? AI decodes complex behavioral signals to reveal the values and mindsets behind decisions, and increasingly, it predicts what audiences will care about next. This allows marketers to deliver timely, relevant messages that resonate with audiences. At Experian, we help brands use these insights to connect more meaningfully and ethically. Takeaway: Experian’s tools help brands uncover audience insights, enabling more meaningful and ethical connections. 2. Where does AI actually save time, and improve results? Running campaigns is time-consuming. Solutions like Agentic AI now orchestrate end-to-end campaign workflows, audience building, trafficking, QA, pacing, and routine optimizations, so teams focus on strategy and creativity. Many leaders (94%) are investing broadly in AI to drive efficiency and impact, and 49% of marketers use it daily for image and video generation, shifting repetitive tasks from people to tools. By quickly combining past and current performance data, AI can pre-optimize before launch and refine mid-flight, while marketers steer the message and experience. "AI uses past campaign data to optimize performance before launch, continues learning during the campaign, and refines strategies based on the insights it generates, driving better results over time.”Howard Luks Takeaway: Experian’s solutions streamline campaign workflows, allowing marketers to focus on creativity and strategy while improving results. 3. How do AI and human strategy work together in real time? AI handles real-time data analysis and optimization, freeing marketers to focus on strategy, messaging, and creativity. By defining audiences once and activating them across platforms, teams can adapt quickly and confidently. At Experian, we combine machine intelligence with human insight to deliver smarter, more agile campaigns. “AI analyzes data, pulls insights, and automates optimizations, allowing marketers to focus on strategy, messaging, and creativity instead of spending time digging through numbers and data."Lizzie Chapman Takeaway: Experian solutions empower marketers to adapt quickly and confidently, combining human strategy with insights. 4. What does privacy-first look like now? Relying on simple, static data points is no longer enough. A modern approach to identity blends deterministic data (like known identifiers) with modeled components, ensuring data remains de-identified where possible. Clear, transparent guardrails, permitted-use policies, retention limits, sensitive-category blocks, and audit trails, help brands balance personalization with privacy, build trust, and respect user choice. "A new blend of identity systems combines deterministic data, known identifiers, and model driven components, creating fresh ways to address identity and activate campaigns with precision.” Vlad Stesin Takeaway: Experian’s privacy-first identity solutions help brands balance personalization with safety, ensuring trust and compliance. 5. Which new data signals matter, and why? AI is unlocking a new generation of data signals, like content context, sentiment, emotional tone, suitability, attention, and commerce intent, that go beyond legacy identifiers like cookies and demographics. These signals can help brand messages appear in the most relevant environments and by high-value audiences. Used well, they improve relevance, avoid placements near unsuitable or off-brand content, and drive stronger campaign outcomes. "Unlocking new data sets (like emotion, sentiment, and context), AI is creating innovative ways to connect client content with advertising opportunities and rethink how we approach the market.” Sam Bloom Takeaway: Experian’s solutions use advanced data signals to help marketers create more effective and innovative campaigns. Why Experian for human-centered AI? We deliver on the promise of AI-powered marketing through five pillars: See audiences clearly across households, individuals, and devices. Recommend next‑best audiences and automate setup for faster execution. Adapt in real‑time to keep relevance high. Innovate responsibly with strong governance and transparency. Plan, activate, and measure campaigns on one unified platform. The future of intelligent marketing AI will keep accelerating, but the goal stands: make marketing more human. Teams that blend privacy‑first identity, predictive insight, AI‑powered simplicity, and real‑time intelligence will earn trust and drive outcomes. Experian helps you bring those pieces together so every campaign moves from assumptions to clarity, and from activity to measurable results. Talk to Experian about building human-centered AI into your marketing strategy AI marketing trends FAQs How does AI help marketers understand audiences better? AI analyzes complex signals, behaviors, values, and mindsets to provide a clearer picture of what matters to audiences. That clarity makes messaging feel personal and relevant. Learn more about Experian’s Digital Graph and how it can help marketers understand audiences better. Where is AI improving campaign efficiency today? Automation reduces manual setup and reporting, so teams focus on strategy and creative. Nearly half of marketers (49%) use AI daily for image and video generation, reflecting this shift. What does “smarter activation across platforms” mean? Smarter activation across platforms means defining audiences once, then carrying them across channels with live feedback, so relevance and suitability stay high. See how Experian enables smarter activation with our data and identity solutions. How is AI changing identity? Privacy‑first identity blends deterministic and modeled components, keeping data de‑identified where possible. Experian’s solutions balance personalization with safety. Learn about Experian’s identity solutions is changing identity. Why is structured data important for AI‑driven marketing? AI systems rely heavily on brand‑managed sources. 86% of citations come from websites, listings, and reviews, so clean, accurate, structured data makes your answers and your brand more discoverable. Discover how Experian supports structured data for AI-driven marketing. Latest posts