Glossary

Cookieless advertising

Advertising
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Written by
Erin Lutenski
Published on
March 22, 2024

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Post-cookie prospecting playbook

Our playbook breaks down the current options available to brands for targeting audiences on the open web — and how they stack up when it comes to reaching net new customers.

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You’ve heard it before: Third-party cookies are on their way out of the Google Chrome browser.

And chances are you just want to know how to continue targeting the right audiences for your brand on the open internet, such as premium online news or CTV — not a history of cookies or how they work. So let’s dive in and answer some of the questions you probably have.

A hammer smashing a cookie into crumbs
Smash your dependence on third-party cookies now to avoid getting left behind when they’re gone for good

How will the end of third-party cookies impact our digital advertising strategy?

There are two main ways you’re likely to be affected: The way you target audiences with personalized ads and the measurement and attribution of your ad efforts. When combined, both contribute to overall ad performance and ROI, so let’s unpack them here:

Targeting and personalization

Because you won’t be able to track user behavior across sites with cookies, you risk having a less complete picture of your audience. This results in lowered targeting precision and a diminished ability to personalize ad experiences.

That’s not to say these things will be impossible to achieve without cookies, but you’ll need to be creative about it. And as third-party data has already started decaying, your cookie-based marketing is likely suffering from this signal loss even before deprecation is complete.

Measurement and attribution

As mentioned in the last section, it’s the ability of cookies to track user behavior across websites which has made them useful to marketers for so long. Cross-site tracking enabled marketers to understand which ad impressions on which channels resulted in a conversion.

At the same time, cookies helped in ensuring that users didn’t see the same ad over a certain number of times in a given period — a practice known as frequency capping.

What alternative solutions can we use to target ads?

Solutions will be suitable to different degrees depending on your brand’s goals. We’ll break down the most popular ones and how they weigh in on the factors listed in the previous section (targeting and personalization + measurement and attribution) as well as what type of audiences they are best suited for (new vs. existing).

We’re only discussing inventories outside walled gardens, like open internet, CTV and other premium digital inventories here, as we’re assuming your brand wants to reach consumers where they spend 66% of their time.

Contextual advertising and buying audience segments

If you know your audience quite well, contextual advertising or buying audience segments from a publisher can be good ways to reach them (both to retain/upsell existing customers or acquire new ones) — if not the most precise. It can also be difficult to measure and attribute ad ROI using these methods. And if your goal is to reach new customers, you might not know their interests well enough yet to buy the right context or segment where they spend their time.

Google’s Privacy Sandbox

To avoid leaving marketers in the lurch, Google has introduced the Privacy Sandbox, consisting of several new APIs and functionalities added to the Chrome browser.

While there are too many of these to dive into them all here, there are two that the company itself has deemed relevant for targeting content and ads: The Topics API and Protected Audience API.

Read our article for a full breakdown of the Privacy Sandbox APIs. But here are the main takeaways: They only offer limited capabilities to prospect for new customers and they are restricted to targeting Chrome users.

Using your first-party data

Fortunately, first-party data — which refers to the data your brand collects directly from your own customers — can address numerous gaps left by walled gardens and contextual advertising. This first-party data provides the most precise foundation for targeting, as it offers insights into the genuine behaviors, preferences, and interactions of your established audience.

The most popular option for first-party data activation is identity solutions. These solutions streamline customer data from multiple sources into a cohesive identity graph, which enables precise targeting across advertising ecosystems. By validating user identities, brands ensure reliable insights from first-party data, fostering trust. However, this approach limits audience expansion as it restricts reach to authenticated traffic and raises privacy concerns under the General Data Protection Regulation GDPR due to its use of hashed email addresses.

There are several other options as well — read our article for a more in-depth explanation of the various approaches available to brands to activate their first party data. In the meantime, here’s an overview list:

  • Customer matching
  • Customer data platforms
  • Google PAIR
  • Traditional data clean rooms
  • Privacy-preserving data clean rooms

These vary quite a lot both in terms of which customers they’ll allow you to reach (new or existing) as well as the amount of privacy they can provide your data.

…But that’s SO many different solutions?!

That’s true. Instead of using a one-size-fits-all solution, which is how many brands approached the use of cookies in their marketing efforts, this new era will need what we like to call the “Swiss Army Knife” approach. This means brands will need a few key tools in their AdTech and/or MarTech stacks, each optimized for a specific purpose.

But there’s one factor you can already consider which might make it easier for you to navigate the different options out there — how the available approaches treat your and your customers’ data.

What steps should we take to ensure compliance with privacy regulations and maintain our customers’ trust?

To be frank, the only way you can be 100% sure what’s happening to your data is by never sharing it with an outside entity. But this drastically narrows your options, so why should you hesitate to share it?

In this new post-third-party-cookie world, first-party data will be more valuable than ever. Never allowing it to be in an environment where it could potentially be used to improve your competitor's targeting efforts is vital. And even more importantly, not sharing it drastically reduces the chance of losing consumer trust as the result of a data breach.

European brands will have to go a step further and ensure that any solutions they implement for cookieless marketing are GDPR-compliant as well.

Some of the solutions above, like purchasing contextual ads or publisher segments and the Privacy Sandbox, put privacy at the forefront. However, they bring drawbacks in terms of limited reach and/or diminished precision.

Where do we go from here?

If your brand is searching for high-precision, high-reach audience activation where your first-party data is not shared with any third parties — not the publisher, not even the solution operator —  Decentriq’s privacy-preserving data clean rooms are an ideal option.

With our clean rooms, you can share data without sharing it. This means you can upload it into the clean room to uncover audience insights for media planning​ without the raw data ever being visible or accessible by your data collaboration partner (like a publisher from our premium publisher network, for example). And with Decentriq’s AI-driven lookalike models, you can reliably prospect for new customers after Google’s cookies crumble.

Contact us to learn more, or download our “Post-cookie prospecting playbook” below for practical strategies on how to continue reaching new customers in a cookieless landscape.

References

Recommended reading

Post-cookie prospecting playbook

Our playbook breaks down the current options available to brands for targeting audiences on the open web — and how they stack up when it comes to reaching net new customers.

Key visual for post-cookie prospecting playbook

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