Navigating A World Without 3P Cookies

It’s an inescapable topic in the paid media industry, and I’ve even written about it in some capacity a few times, but recent news has sparked continued discussions around how brands can navigate through a digital ecosystem without third party cookies.

Ad Exhanger recently covered Google’s test of its own privacy-friendly third party ad tech, which I believe warrants further discussion around the tactical opportunities marketing departments can take advantage of to prepare for a world without 3P cookies. Two of the largest areas impacted by Chrome’s looming update are audiences and measurement.

Audiences

Given the historical pervasiveness of 3P cookies across the internet, brands could rely on the data captured by these cookies to develop high performing audiences. Whether that was an effective in-market segment, or a niche retargeting cohort, advertisers will now have to change how their audiences are constructed.

To evaluate how audiences are built, we’ll need to examine the different types of privacy-friendly data that marketers will have available to them post-cookie update.

0P Data

This data type consists of any information that users voluntarily give to a brand. 0P data can take the form of a name, email, address, product preferences, and just about anything else that a consumer is willing to share with a brand when asked. Common methods to capture 0P data include quizzes and form submissions in exchange for some type of content, personalization, or discount.

Given that 0P data has to be actively shared by a user, and is typically only collected on digital properties owned or managed by a brand, this data type tends to be the lowest in volume. However, it is often some of the highest quality data that a marketing program can collect.

For example, if someone visits the Zappos site and responds to a pop-up offer by providing the information that they:

• Are a male

• Wear size 11 shoes

• Run three times a week

Zappos can craft marketing campaigns that are significantly more relevant to this user, and others like him. Which of the below ad headlines do you think would be more appealing to this person?

“Get your new summer shoes!”

or

“We’ve restocked our size 11 men’s running shoes just in time for those summer runs!”

Chances are that the more personalized and relevant headline will drive stronger engagement with users. Capturing 0P data is a big opportunity for brands, and even simple information like what I outlined above can change how campaigns are structured.

1P Data

Similar to 0P data, first party data is information captured by a brand on its owned and operated properties, but the difference here is that this data is observed rather than overtly shared.

A classic example of 1P data is the set of actions users take on a website that can be observed through Google Analytics. 1P data on its own may be more limited without 3P cookies, so it can become more useful when paired with 0P data.

For example, if a user is logged in to the Zappos website, they might not be served a pop-up offer so that they have an improved user experience. However, the Zappos team might send their own internal user IDs to their GA4 property to observe that a specific user, or group of users, navigated to the men’s running shoes category and was selecting a size 11 when checking for product availability. The marketing team can then create a cohort of users who exhibited similar behaviors, and attribute these actions to their logged-in accounts for marketing efforts across platforms using whatever identifiers they have available to them.

I envision that brands will lean further into customer data platforms (CDPs) in the coming months since this technology will help them to take advantage of all of the 0P and 1P data that they collect.

2P Data

2P data is a combination of 0P and 1P data that simply belongs to a third party. An example of 2P data in the paid media world would be the targeting capabilities that Amazon and LinkedIn have. Both platforms can observe actions that logged-in users take, and share aggregated behavior with advertisers for targeting purposes. In some cases, even the user demographic data alone is robust enough for effective targeting without adding in any observed data points.

The reach of 2P is similarly limited to the channels owned by the data provider, but I predict that 2P will serve as an even greater competitive advantage for these ad platforms in the near future. If advertisers start to see stronger performance in platforms with robust 2P data targeting options, then a greater share of their investment will be allocated to channels.

3P Data

This is a data type that many advertisers rely heavily on, and it is also the type of data that will be impacted the most by 3P cookie deprecation (naturally). 3P data is aggregated across multiple sources, and shared between parties across the internet. While it’s been useful for advertisers, consumers haven’t always felt comfortable knowing how much information ad servers were collecting about them. That’s the driving force behind Chrome’s decision to disable 3P cookies late next year.

However, Google wouldn’t remove a core feature from its largest source of revenue without having some sort of backup plan in place. The ad giant has been testing a series of different approaches in recent months to prepare marketers for a world without the 3P audiences they’ve grown so accustomed to using in recent years.

The most recent iteration of this test compared a standard 3P cookie targeting strategy to one that used site-based contextual data, publisher first party IDs where available, and data from the Topics API. I won’t go into the results in depth, but while CTR and CVR were only moderately impacted for the privacy-friendly test cell, one big call out is that the test campaign still used 3P cookies for attribution, retargeting, and frequency capping… Not necessarily the cleanest experiment set up here.

With all of that said, there isn’t a solid 3P targeting solution in place at the moment. Brands might start to rely on a wider variety of 2P data to reach their cold audiences in the near future.

However, I wouldn’t count Google out when it comes to building an innovative 3p targeting solution just in time. There are billions of dollars on the line after all.

Performance Measurement

It’s one thing to have an understanding of how 0P, 1P, and 2P data can help to create audiences, but it’s another endeavor entirely to measure the performance across paid media channels. The advertising industry has leaned on cookies for far too long to determine that an action was completed, and what marketing activities contributed to that action.

Determining That An Action Was Completed

Most ad platforms have used, or still currently use, some sort of third party pixel that is placed on an advertiser’s website to track conversions. This pixel sends information back to the ad platform for reporting and optimization purposes. Without the use of third party cookies, all of this information disappears.

This means that both ad platforms and advertisers need to begin leveraging other methods to track events on a website. Luckily, there are plenty of solutions already available.

The naming of these solutions might vary depending upon where you look, but if the ad platform you work with offers:

• A conversion API

• Enhanced Conversions solution

• Offline conversion import

Then I would start to get comfortable using that feature sooner rather than later. These conversion tracking methods are privacy-friendly, but not always advertiser-friendly. The implementation of these solutions might require help from a developer in certain instances, as well as routine management of internal customer/lead data.

Afterall, customer data is the centerpiece for these future-proof conversion tracking technologies. In their own way, they each pass hashed customer data between a brand’s digital properties, and the ad platform to confirm that a conversion took place.

Any form of server-to-server tracking (or its varying iterations) requires advertisers to maintain a more robust data infrastructure. This is actually a good thing, as it will force marketing programs to use this modern technology to measure performance. CDPs can play a critical support role in this function, which is another reason why I believe they’ll become more widely adopted.

Given the runtime typically associated with the implementation of these solutions, starting now might help to prevent your team from falling behind and flying blind next year.

Identifying What Media Contributed To An Action

Despite 3P cookies still functioning to some extent on Google Chrome, the advertising industry is already seeing a loss of signal as user journeys become more and more widely dispersed.

I’ve written about potential privacy-friendly measurement solutions before, so I won’t spend a lot of time here. In short, based on how complex your marketing program is, you might look to leverage a combination of incrementality testing and media mix modeling to understand the impact media has on your business.

In the end, we won’t be able to escape the death of the 3P cookie. However, that’s not necessarily a bad thing. There are already multiple alternative approaches to both audience building and performance measurement. All of which can actually provide more clarity to businesses for better decision making moving forward.

Have questions, considerations, or critiques? I’d love to hear them! If you’re reading this via email, just hit respond. Otherwise, you can find me on LinkedIn and X (Twitter).