The departure from third-party cookies is no longer a theoretical debate. It is happening gradually but irreversibly – driven by regulation, technological changes and a significantly increased awareness of data protection. What was long considered a standard practice is increasingly losing its importance. However, this change is by no means a technical downgrade, but rather a strategic opportunity. The crucial question is no longer ‘How can cookies be replaced?’ but ‘How can relevance, reach and measurability be achieved in a new, sustainable ecosystem?’ The real upheaval lies less in the elimination of an identifier than in the reassessment of how digital advertising should fundamentally work.
From replacement thinking to ecological restructuring
In the early stages of the cookie debate, the focus was on finding alternatives that were as similar as possible. New IDs, login alliances and probabilistic models were intended to continue the familiar logic of individual recognition as seamlessly as possible, but often with limited success and new regulatory doubts.
However, a deeper pattern is becoming increasingly apparent: the challenge is less technical and more structural in nature. Tomorrow’s advertising will no longer function primarily through the seamless tracking of individual users, but rather through the intelligent interplay of context, high-quality data and precise control.
A fixed concept of identity is being replaced by a dynamic understanding of situations. We no longer address people because we ‘know who they are.’ We reach them because we understand the situation they are currently in and the mindset they bring with them. This ecological transformation does not mean replacing a dominant mechanism. It represents the transition from monolithic to modular, resilient systems.
Contextual Targeting 2.0: Relevance through context
Contextual targeting is one of the oldest disciplines in digital advertising and, at the same time, one of the most underestimated. Modern approaches go far beyond simple keyword logic. They analyse semantic relationships, evaluate the editorial quality and tone of an environment, and even take the usage situation into account.
The advantage of this is as simple as it is compelling: relevance arises directly and organically from the environment itself. A reader of an article about sustainable travel is open to relevant offers at that moment – regardless of their cookie history. This logic is not only effective, but also privacy-friendly. The key to success lies in precision: only through clean and in-depth classification of content can contextual targeting unfold its full potential to reduce wastage and increase user acceptance.
First-party data: a foundation built on responsibility
First-party data is rightly considered the gold standard of the cookie-less era. As information voluntarily provided from direct customer relationships, it is of the highest quality, trustworthiness and relevance. But simply owning it is not a competitive advantage. Its true value only unfolds through strategic use and integration.
Although many companies have extensive data sets at their disposal, they fail due to fragmented silos, a lack of structure or insufficient integration into media and campaign processes. At the same time, demands for transparency and data governance are growing, and users expect recognisable and fair value in return for their data. Successful first-party strategies therefore require not only robust technology, but also consistent, trust-building communication.
Cohorts & Privacy-Preserving APIs: Scaling without individualisation
Cohort-based approaches and privacy-preserving APIs offer a promising way to increase reach beyond one’s own data pool. Instead of targeting individual users, people are addressed as part of statistically defined, interest-based groups.
These models are scalable, robust in regulatory terms and reduce dependence on fragile personal identifiers. At the same time, they require a rethink in planning: target groups become more abstract and optimisation processes are less granularly focused on individuals. In the long term, such approaches can form a stable, data protection-compliant basis for broadly effective campaigns – not as a panacea, but as an essential building block in the overall setup.
Data Clean Rooms: The architecture for trustworthy collaboration
Data clean rooms are becoming increasingly important in situations where multiple parties want to gain insights from their data without having to exchange the underlying sensitive information itself. They enable analysis, overlap measurement and success attribution in a controlled and secure environment.
However, the added value does not arise automatically from the technology itself. Data clean rooms are precise tools for clearly defined issues, such as campaign optimisation, cross-channel management or linking advertising impulses with sales results. The decisive factor is the ability to translate aggregated insights into concrete operational decisions.
Measurability reimagined
The elimination of personal identifiers is putting established measurement and optimisation models under increasing pressure. Attribution is becoming more complex, traditional KPIs are losing their precision, and the advertising impact can be less clearly attributed to individual contacts.
At the same time, new measurement logics are emerging in which aggregated models, probabilistic approaches and qualitative indicators are increasingly coming to the fore. Instead of precise allocation, the focus today is on robust impact models that deliver reliable results even under restrictive conditions.
This changed view of measurability has a direct impact on operational control, as traditional frequency capping, which is based on individual recognition, is increasingly reaching its structural limits. Identifier-independent approaches such as AnyID frequency capping show that contact dosage is also possible without personal profiles – not at the level of individual users, but via consistent, aggregated system logic. Frequency is thus evolving from an individual control variable to a strategic control dimension.
It is clear that measurement and control can no longer be viewed in isolation. They are part of a larger context in which different approaches must be interlinked.
"AnyID Frequency Capping" has been very well received in the market. It is clear that there is a demand for this.
Interaction instead of individual solutions
Practice clearly shows that no cookie-free approach can have a lasting effect on its own. This effect only arises from the intelligent interaction of high-quality context, strategically used first-party data, scalable anonymised models and adapted measurement methods. Future-proof campaigns must be cross-channel, inventory-flexible and regulatory-resilient. The underlying technology must be able to combine different signals and models into a coherent strategy without relinquishing control over data and processes.
The future of digital advertising therefore does not lie in the search for the next singular standard. It lies in the ability to deal confidently with diversity. Companies that rely on multiple interoperable approaches today and have mastered their interaction are not building short-term transitional solutions. They are creating genuine resilience to regulatory, technological and market changes.
Cookies have long been a dominant but fragile mechanism. Their abolition does not mean a loss, but rather an opportunity for a more sustainable, transparent and robust advertising ecosystem. The decisive factor will not be who sets the next standard, but who has learned to rethink relevance under new conditions.
