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The future of identity in cookieless advertising

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

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.

Check out more Cannes content:

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How contextual advertising addresses signal loss

Note: While third-party cookies are no longer being phased out, this webinar was recorded in 2023 when cookie deprecation was still a key industry focus. The strategies discussed reflect that time frame and remain relevant for addressing broader signal loss challenges. With major browsers discontinuing support for third-party cookies, marketers must rethink how to identify and engage their audiences. Contextual advertising offers a privacy-safe solution by combining contextual signals with machine learning to deliver highly targeted campaigns. In a Q&A with our experts with eMarketer, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions at Experian, and Alex Johnston, Principal Product Manager at Yieldmo, we discuss how contextual advertising addresses signal loss, improves addressability, and delivers better outcomes for marketers. The macro trends impacting marketers How important is it for digital marketers to stay informed about the changes coming to third-party cookies, and what challenges do you see signal loss creating? Jason (Experian): Third-party cookies have already been eliminated from Firefox, Safari, and other browsers, while Chrome has held out. It’s just a matter of time before Chrome eliminates them too. Being proactive now by predicting potential impacts will be essential for maintaining growth when the third-party cookie finally disappears. Alex (Yieldmo): Third-party cookie loss is already a reality. As regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) take effect, more than 50% of exchange traffic lacks associated identifiers. This means that marketers have to think differently about how they reach their audiences in an environment with fewer data points available for targeting purposes. It’s no longer something to consider at some point down the line – it’s here now! Also, as third-party cookies become more limited, reaching users online is becoming increasingly complex and competitive. Without access to as much data, the CPMs (cost per thousand impressions) that advertisers must pay are skyrocketing because everyone is trying to bid on those same valuable consumers. It’s essential for businesses desiring success in digital advertising now more than ever before. Solving signal loss with contextual advertising How does contextual advertising help marketers engage audiences with new strategies like machine learning and artificial intelligence (AI)? Jason (Experian): Contextual advertising helps marketers engage audiences by combining advanced machine learning with privacy-safe strategies. We focus on using AI and machine learning to better understand behavior, respect privacy, and deliver insights. As third-party cookies go away, alternative identifiers are coming to market, like Unified I.D. 2.0 (UID2). These are going to be particularly important for marketers to be able to utilize them. As cookie syncing becomes outdated, marketers will have to look for alternative methods to reach their target audiences. It’s essential to look beyond cookie-reliant solutions and use other options available regarding advertising. Alex (Yieldmo): There’s been a renaissance in contextual advertising over the last couple of years. Three key drivers are shaping this shift: The loss of identity signals is forcing marketers to rethink how they reach audiences. Advances in machine learning allow us to analyze more granular contextual signals, identifying patterns that are most valuable to advertisers. Tailored models now use these signals to deliver more effective campaigns. This transformation is occurring because of our ability to capture and operate on richer, more detailed data. Reach consumers with advanced addressability How does advanced contextual advertising help marketers reach non-addressable audiences? Jason (Experian): Advanced contextual advertising helps marketers reach non-addressable audiences by taking a set of known data (identity) and drawing inferences from it with all the other signals we see across the bidstream. It’s about using a small seed set of customers, those who have transacted with you before or match your target audience, and training contextual models to make the unknown known. Now we can go out and find users surfing on any of the other sites that traditionally don’t have that identifier for that user or don’t at that moment in time and start to be able to advertise to them based on the contextually indexed data. Alex (Yieldmo): I think the exciting opportunity for many people in the industry is figuring out how to reach your known audience in a non-addressable space, that is based on environmental and non-identity based signals, that helps your campaign perform. Machine learning advancements allow you to take your small sample audience and uncover those patterns in the non-addressable space. High-quality, privacy-resilient data sets are critical for building these campaigns. Companies like Experian, with deep, rich training data, are well positioned to support advertisers in building extension audiences. Creative strategies that improve ad performance Why does creative strategy remain essential for digital advertising success? Jason (Experian): Creative strategy remains essential because it provides valuable signals for targeting and engages audiences effectively. In this advanced contextual world, good creative in the proper ad format that you can test and learn from is paramount. It comes back to that feedback loop. We can use that as another signal in this equation to develop and refine the right set of audiences for your targeting needs. Alex (Yieldmo): Creative and ad formats are powerful signals for understanding audience engagement. At Yieldmo, we collect interaction data every 200 milliseconds, such as scrolling behavior or time spent on an ad. This data fills the gap between clicks and video completions, helping us build models that predict downstream actions. Tailoring creative to specific audience groups has always been one of the best ways to improve performance, and it remains essential in this new era of contextual advertising. Throughout my career, I learned that designing or tailoring your creative to different audience groups is one of the best ways to improve performance. We ran many lift studies with analysis to understand how you can tailor creative customized for individual audiences. That capability and the ability to do that on an identity basis is. Our recommendations for actionable marketing strategies Do you have recommendations for marketers building out their yearly strategies or a campaign strategy? Jason (Experian): My recommendation for marketers building out their yearly strategies is to be proactive and start testing and learning these new solutions now. I mentioned addressability and being in the right place at the right time. That’s easier in today’s third-party cookie world. But as traditional identity is further constricted, you will have these first-party solutions that will not be at scale, so you’re less likely to find your user at the scale you want. It would be best if you thought about how to reach that user at the right place at the right time. They may not be seen from an identity basis. They might not be at the right place at the right time when you were delivering or trying to deliver an ad. But you increase your chance of reaching them by building these advanced contextual targeting audiences using this privacy-safe seed ‘opted-in’ user set; this is a way to cast that wider net and achieve targeted scale. Alex (Yieldmo): Build your seed lists, test your formats with different audiences, and understand what’s resonating with whom. Take advantage of some of the pretty remarkable advances in machine learning that are allowing us, really, for the first time to fully uncork the potential and the opportunity with contextual in a way that we’ve never done before. Contact us About our experts Jason Andersen Senior Director, Strategic Initiatives and Partner Solutions, Experian Jason Andersen heads Strategic Initiatives and Partner Enablement for Experian Marketing Services. He focuses on addressability and activation in digital marketing and working with partners to solve signal loss. Jason has worked in digital advertising for 15+ years, spanning roles from operations and product to strategy and partnerships. Alex Johnston Principal Product Manager, Yieldmo Alex Johnston is the Principal Product Manager at Yieldmo, overseeing the Machine Learning and Optimization products. Before joining Yieldmo, Alex spent 13 years at Google, where he led the Reach & Audience Planning and Measurement products, overseeing a 10X increase in revenue. During his time, he launched numerous ad products, including YouTube’s Google Preferred offering. To learn more about Yieldmo, visit www.yieldmo.com. About Yieldmo Yieldmo is an advertising platform that fuses media and creative to meet audiences in the moments that matter. Using proprietary data and AI, Yieldmo uses advanced targeting to deliver context-aware creative when and where it’s most effective, all while respecting user privacy. The result: ads that belong on inventory brands trust. 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