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The future of identity in cookieless advertising

Published: August 15, 2023 by Hayley Schneider, Content Marketing Manager

The next era of identity is here

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.

Watch the recording of our Cannes panel, "What does the future of identity hold?"

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

Cannes Lions 2023 panelists: What does the future of identity hold?

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.

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In addition, we offer the ability to create custom segments across verticals.  Our intent-based audiences, built from contextual and engagement signals, help buyers reach consumers on CTV, desktop, or mobile devices with scale.  Being part of Experian’s data marketplace accelerates access to these audiences, drives better ROI, and helps brands future-proof their strategies today. Retail demand signals Retail brands are racing toward privacy-safe, first-party data. Which 33Across retail datasets or segments are experiencing the highest demand, and what makes them a must-have?  Retail marketers are leaning into contextual and behavioral intent signals to complement their first-party data strategies. At 33Across, we’re seeing high demand for segments tied to shopping intent, including in-market consumers browsing for categories like fashion, home goods, electronics, and health & wellness. What makes these segments essential is their real-time nature – they can capture consumer interest as it happens. For retail brands looking to expand their reach while respecting privacy, our segments offer scalable, actionable intent that drives results. B2B without cookies Reaching real B2B decision-makers at scale is tough with or without signals. How does 33Across deliver both precision and reach in this environment?  B2B marketing often struggles with balancing scale and specificity. 33Across addresses this by combining contextual precision with AI-modeled behavioral signals; this segment approach reaches professionals actively engaging with relevant content and topics, even in environments where IDs are unavailable. Marketers gain access to more signals and, in turn, better reach from 33Across’ unique publisher integrations and audience curation built from machine learning and AI. We surface intent through content consumption patterns and contextual engagement, unlocking valuable, privacy-safe signals at scale. Allowing B2B marketers to reach real decision-makers in a signal-sparse world.  Use cases With retail, B2B, and beyond, can you share an example of how brands in these verticals are utilizing your audiences? Top brands that have a user-focused approach use 33Across audiences to drive scale; performance. These brands enable our segments to precisely reach the right users across devices and increase conversion rates; brand awareness. By reaching the right users, brands have higher conversion rates and increase campaign efficiency. Supply path innovation As identifiers disappear, advertisers are looking for scalable, privacy-safe ways to reach real people. How is 33Across helping unlock more addressable inventory and drive performance? By combining contextual, semantic, and engagement-based signals, we deliver intent-based targeting that performs across CTV, display and video. Higher addressability helps marketers not only extend their reach but also deliver personalized messaging across digital channels in a privacy-compliant way.  Contact us FAQs How can advertisers reach audiences without traditional identifiers?  By using contextual and engagement-based signals, advertisers can target consumers across CTV, mobile, and desktop in a privacy compliant way, even as identifiers become less available.  What audience segments are most in demand for retail marketers?  Segments tied to shopping intent, such as consumers browsing fashion, electronics, or health products, are highly sought after because they capture real time interest and drive results.  How can B2B marketers find decision-makers without cookies?  Combining content engagement patterns with machine learning allows marketers to reach professionals actively engaging with relevant topics, even in environments where IDs are unavailable.  What makes privacy safe audience targeting effective?  Privacy safe targeting uses real time contextual and behavioral signals to deliver relevant messaging across devices and channels without compromising consumer trust.  How can real-time intent signals drive demand?  Real time intent signals allow advertisers to capture consumer interest as it happens, helping demand side platforms and brands deliver timely, relevant ads that increase engagement and drive conversions across devices like CTV, mobile, and desktop.  About our expert Allison Dewey, Director of Data and Curation, 33Across Allison Dewey is the Director of Data & Curation at 33Across, where she oversees data partnerships, integrations, and supply-side curation. With a deep expertise in audience targeting and signal optimization, Allison plays a key role in connecting data into the programmatic world. Allison holds a Bachelor\’s degree in Psychology from Bates College. About 33Across Rooted in over 15 years of data expertise, 33Across harnesses signals to enrich and expand marketers’ audiences and reach them wherever they consume content. Built from over 300 billion proprietary data signals, we apply machine learning and AI to create over 1,500 B2C and B2B segments using privacy-first principles to reach audiences.   Latest posts

Oct 22,2025 by Experian Marketing Services

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