Synthetic Users and ID Pooling: Remarketing in the cookieless Era

The advent of the GDPR and cookie banners is increasingly making it easy for web users to decline consent to tracking and data processing. Current estimates suggest businesses are missing 30% to 50% of web data due to a lack of user consent. 

This is essential data for analysis, personalization, and marketing optimization. Digital marketers need help gaining insights into customer behaviour and effectively targeting their campaigns. There is reason to believe this trend will continue as data protection agencies effectively outlaw dark patterns in cookie banners. 

Marketers are missing data due to the website users’ right to withhold consent. Additionally, browser developers have imposed stricter rules governing the placement of cookies in the users’ browsers. Safari, Firefox and Edge significantly restrict third-party cookies' lifetime or even delete them outright after every session. Popular adblockers block third-party cookies as well, further diminishing the pool of users that marketers are allowed to track. 

This is a severe problem for remarketing (or retargeting). Remarketing has become one of the most effective digital marketing methods in the past two decades. With this technology, users can be targeted and marketed to across websites and platforms. Since remarketing relies on third-party cookies, cookie restrictions combined with declined consent means that remarketing today relies only on the data of as little as 20 per cent of users – much too little to market to audiences effectively.  

Once Google’s Chrome ends the support for third-party cookies in 2024, remarketing as it is now known, will no longer be possible. 

So what will follow?

Traditional remarketing is on its way out – but this could be a good thing. First, technologies based on third-party cookies are today deemed intrusive on user privacy by tracking them across the web and collecting vast amounts of data. New regulatory regimes like the GDPR or ePrivacy in the EU seek to reign in these practices. 

Secondly, cookieless remarketing technologies that preserve user privacy are on the rise. Google is developing their Privacy Sandbox for the privacy-compliant targeting of user groups. 

Two other new technologies build on advancements in AI and synthetic data generation. They are called synthetic users and ID pooling. 

They promise to restore the data lost to declined consent and cookie prevention in a manner that protects user privacy and complies with data protection laws like the GDPR in Europe – all while enabling remarketing to website-specific audience segments.

To better explain how synthetic users work, we must differentiate between two types of users: 

1. those who give consent to be measured, who can be addressed via remarketing as usual. Let’s say, from experience; these are 40% of your users – this is a realistic average consent rate when users are given the clear choice to decline all consent without dark patterns in the mix. 
2. Those who do not give consent. 

So, how can one measure the behaviour of the 60% without infringing on their privacy rights?

A solution for this problem is turning these anonymous users into synthetic users. Leveraging AI, it is possible to model these new users so that they cannot be traced back to real people but behave almost the same way as their real-life counterparts. 

This can be done by identifying which signals in the consented cluster of users best predict the behaviour of the cluster of users that have not given consent. This requires that the former cluster is measured with a high data quality and that the latter users’ behaviour must be measured in an anonymized matter for a limited set of fundamental metrics which comply with privacy regulations like the GDPR. Both these requirements can be fulfilled with advanced server-side tracking technology. 

In client-side web tracking, data collection and event tracking are initiated directly within the user's browser using JavaScript. This method typically involves JavaScript tags or pixels loaded and executed in the user's browser. As a result, data is sent from the user's browser directly to the analytics provider. While this approach can capture a wide range of user interactions, including mouse movements, clicks, and form submissions, it is more susceptible to being blocked by ad blockers or tracking preventions in browsers that restrict tracking scripts, and it often relies on third-party cookies, which are facing increasing restrictions in many modern browsers.

Server-side web tracking, on the other hand, shifts the data collection process to the web server instead of the user's browser. In this method, events are sent from the website's server directly to the analytics provider's server. This means the website's server can aggregate, modify, or filter data before sending it to the analytics provider, offering more control and accuracy. Server-side tracking is more robust and much less prone to issues related to browser restrictions, ad blockers, or third-party cookie limitations, collecting more data and better data quality that can be used for advanced AI applications like synthetic users.  

The technology behind synthetic users enables marketers to derive valuable insights from the entirety of website data, all while adhering strictly to data protection regulations. 

A comprehensive data collection process enables marketers to refine their marketing strategies based on data insights. They can analyze user behavior, identify efficient sales channels, understand conversion funnels, and make data-driven decisions. The ultimate goal is to enhance both the Return on Investment (ROI) and the efficiency of campaigns.

However, this data must be compatible with performance marketing platforms in a privacy-compliant way. Enter ID pooling.

With synthetic users, website data can be restored. But it must still be compatible with performance marketing platforms like Google Ads. This traditionally involved sharing click IDs collected on the website with these platforms to track the customer journey and conversions for ad optimization and retargeting. However, sharing identifiable information like click IDs is a major data protection hazard. 

This problem is solved with ID pooling. With ID pooling, synthetic and natural website users are first segmented according to their marketing-relevant traits. Then, collected click IDs of these segments are pooled together and randomly assigned to users in the respective pools. These IDs are then transmitted to the ad platforms. In consequence, the platforms never receive the correct ID for a given user, protecting the user’s identity, but as the received ID stems from the same segment pool, the similarity is significant enough to enable effective remarketing within this and similar segments. 

While synthetic users and ID pooling offers the opportunity for cookieless remarketing, there is the drawback to consider that it will not be able to provide the granular targeting and ad personalization on a user-level that we have become accustomed to. This was a feature of the old ad ecosystem on the web that relied on third-party cookies. Without them, and with stringent regulations now in place, remarketing will likely never again be able to provide this value. 

But then again, the limitations of traditional remarketing already result in increased campaign inefficiencies and a notably higher Cost Per Acquisition (CPA) due to cookie banners, ad blockers and tracking prevention. 

ID pooling technology provides visitors personalized content and includes them in retargeting campaigns. It respects users' privacy while delivering tailored experiences, lowering Cost Per Acquisition (CPA), and increasing Return on Ad Spend (ROAS). 

In a world where data protection and customer engagement are paramount, synthetic users and ID pooling present an innovative cookieless remarketing solution to digital marketing's challenges. These technologies allow businesses to engage with customers effectively and legally without compromising privacy. The leading solution for synthetic users and ID pooling is the server-side tracking provider JENTIS. 

For more information or to gain early access for your business to these emerging technologies, visit JENTIS's website.