Cohort targeting: the future of ad targeting without cookies?

Cohort targeting: the future of ad targeting without cookies?

Les points clés

Cohort targeting provides a balance between ad personalization and privacy without individual user tracking.
Complying with data protection regulations, such as the GDPR, it represents an alternative to third-party cookies.
Although less accurate than individual targeting, it offers new opportunities for innovative and ethical advertising strategies.
Its effectiveness depends on analyzing big data to create user segments based on common interests or behaviors.
Faced with changes in the advertising industry, it is a step towards practices that are more respectful of confidentiality.


The advertising industry is booming, but it is also undergoing a metamorphosis. Long dominated by third-party cookies, powerful tools for tracking and analyzing online user behavior, it is now facing a major paradigm shift. The current transition is driven by an increased collective awareness of the importance of privacy, as well as by the evolution of global regulations such as the GDPR in Europe. In response, the industry is turning to more privacy-friendly ad targeting methods, with cohort targeting emerging as a promising solution.

But what exactly is cohort targeting? Unlike traditional cookie-based targeting, which relies on individual and often intrusive tracking of users' online habits, cohort targeting takes a more comprehensive and anonymous approach. It groups users into “cohorts” based on common criteria such as similar interests or behaviors, without identifying or tracking each user individually. This method thus offers an alternative that is more privacy-friendly, by allowing advertisers to serve relevant ads without encroaching on the privacy of individuals.

Cohort targeting therefore represents a balance between effectively personalizing advertising campaigns and respecting growing concerns about data privacy. This introduction to the foundations and promises of cohort targeting aims to shed light on how it works, its benefits, and its potential impact on the future of ad targeting.

Understanding cohort targeting

👉 How cohort targeting works

Cohort targeting marks a significant evolution in the way online advertising is approached. Instead of tracking individuals, this method groups users into segments or “cohorts” based on common criteria. These criteria may include shared interests, similar browsing behaviors, or consumer preferences. For example, a cohort may consist of users who have visited technology websites or who have shown an interest in specific topics such as sustainable development.

The process starts with analyzing aggregated data trends to identify patterns of behavior. Then, users with similar behaviors are grouped into the same cohort. Unlike methods based on third-party cookies, cohort targeting does not require identifying or tracking users at an individual level, making it less intrusive in terms of privacy.

👉 Benefits of cohort targeting

  • Respect for privacy: One of the main benefits of cohort targeting is its ability to respect the privacy of users. By avoiding individual follow-up, this method reduces concerns about the collection and use of personal data, which is particularly relevant in the context of data protection regulations.
  • Improved relevance: Although less personalized than individual targeting, this approach can offer improved advertising relevance. Ads target groups of users with similar interests, increasing the chances of ad content being relevant and engaging for a larger segment of the audience.
  • Regulatory compliance: With regulations such as the GDPR in Europe, cohort targeting offers a compliant alternative. By minimizing the collection of personal data and focusing on anonymous, aggregated data, advertisers can better navigate the complex regulatory landscape for online advertising.
  • Innovative targeting opportunities: Cohort targeting paves the way for creative approaches in digital advertising. Advertisers can explore new ways to connect with audiences based on collective interests or behaviors, rather than individual profiles.

👉 The disadvantages of cohort targeting:

  • Lower accuracy than individual targeting: Cohort targeting, by grouping users based on similar interests or behaviors, lacks the granular precision of targeting based on third-party cookies. This may result in ads that are less personalized for the individual user.
  • Difficulties in segmenting the audience: Identifying specific and relevant audience segments can be more complex with cohort targeting. Nuances and variations within the same cohort can be ignored, reducing the effectiveness of targeting for certain very specific products or services.
  • Limits in retargeting: Cohort targeting is less effective for strategies such as retargeting, which require specific data on individual user actions and preferences.
  • Dependence on large volumes of data: To be effective, cohort targeting requires large amounts of data to identify trends and create meaningful segments. This can be a challenge for advertisers with limited access to large amounts of aggregated data.
  • Lack of customization for small niches: Businesses targeting very specific niches may find cohort targeting less useful because it is more tailored to common interests and behaviors rather than the unique needs of small, specific groups.
  • Risks of reduced relevance: Without a deep understanding of the various cohorts, there is a risk of running ads that are not entirely relevant to all members of a given cohort, which can reduce the overall effectiveness of the campaign.


In short, cohort targeting represents a promising method for advertisers seeking to combine advertising effectiveness with respect for user privacy. This approach meets the growing demand for more ethical and privacy-compliant advertising targeting methods, while maintaining much of the effectiveness of traditional advertising strategies. However, it is important to recognize and address its limitations in terms of precision, segmentation, and personalization. Advertisers need to weigh these disadvantages against the benefits to determine the best strategy for their specific needs.

Cohort targeting in practice

👉 Application examples

Cohort targeting is already being adopted in various aspects of online advertising. A notable example is Google's initiative with “Topics.” Topics is a system offered by Google as part of its Privacy Sandbox, which replaces individual tracking with third-party cookies. It works by associating users with topics of interest based on their browsing history, without tracking them individually. For example, if a user frequently visits sites related to running, they could be placed in a “sport and fitness” cohort. Advertisers can then target this cohort to deliver relevant ads on sports products, without knowing the specific identity of the user.

👉 Comparison with third party cookies

Unlike targeting based on third-party cookies, where individual browsing data is used to create personalized ads, cohort targeting focuses on groups of users with common interests. While targeting with third-party cookies can provide extremely specific personalization, it poses significant privacy and regulatory compliance issues. On the other hand, cohort targeting offers a more favorable balance between advertising relevance and respect for privacy.


Cohort targeting, as an emerging alternative to targeting based on third-party cookies, represents a significant evolution in the field of online advertising. This new approach, which focuses on grouping users based on their common interests and behaviors, provides a balance between the need for advertising effectiveness and the growing need to protect user privacy.

Future perspectives:

The future of ad targeting is moving towards solutions that are more privacy-friendly while remaining effective. Cohort targeting is an important step in this direction, signalling a shift towards more ethical and transparent advertising practices. With the increasing adoption of advanced technologies like artificial intelligence to refine targeting within cohorts, we can expect to see this method gain in sophistication and efficiency.

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