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solutions for the Cookieless
Ecosystem
Trusted by fast growing franchise brands
Context & Mission
The adtech landscape is undergoing significant change. The end of the third-party cookie era, which began several years ago, is now taking shape, disrupting targeting strategies and advertising performance measurement.
From the introduction of Intelligent Tracking Prevention (ITP) in 2017 to the gradual rollout of the Privacy Sandbox by Google, market players are being forced to rethink their approaches to ensure the effectiveness of their campaigns while complying with new privacy requirements. In this context, we position ourselves as a transition facilitator towards a cookieless ecosystem.
- Integrate advanced technologies in DCO and probabilistic tracking.
- Build robust strategies for retargeting, creative automation, and performance measurement without relying on third-party cookies.
EASIFY Solution
DCO Cookieless Retargeting
With the end of third-party cookies, retargeting must evolve. EASIFY is based on a probabilistic approach, combining multiple signals to efficiently recognize and activate audiences while adhering to privacy and regulatory compliance requirements. This solution allows you to:
EASIFY offers a robust and scalable alternative for brands wishing to preserve campaign effectiveness in a cookieless world.
Dynamically personalized ads without relying on third-party cookies.
Leverage contextual and first-party signals to maximize campaign relevance.
Maintain reliable performance tracking, through advanced conversion modeling.
Benefits of Our EASIFY Cookieless Solution
Seamless
Transition
Regulations
Compliance
Scalable
Alternative
Intelligent Signal Collection
When a user visits a site, the COOL Media Site Tracker plays a central role in collecting and analyzing available information to feed EASIFY. It relies on two complementary data types:
User ID
If a user ID is available (via a first-party cookie or an alternative identification solution like ID), it is used to recognize the audience.
Probabilistic Signals
If no User ID is accessible, the Site Tracker collects and analyzes a combination of contextual and technical signals to probabilistically identify the audience. These signals include elements such as the device, approximate location, browser characteristics, and site interactions.
Cookieless Retargeting Activation
For each impression, EASIFY follows this logic:
- If a User ID is available, it is used to personalize and target the ad.
- If no User ID is available, EASIFY evaluates the available probabilistic signals.
- If the signals are relevant, they are used to dynamically personalize the ad message.
- If no relevant signals are available, no user data is collected.
Thanks to this mechanism, EASIFY ensures high-performance cookieless activation, providing advertisers with continuity in targeting and personalization even in a third-party cookie-free environment.
Ultra-Flexible Compatibility
EASIFY is designed to be interoperable with all cookieless retargeting strategies and stakeholders:
- Compatible with First ID, ID 5, Utiq, and first-party identification solutions.
- Works with cross-device solutions to ensure audience continuity.
- Integrates the principles of the Privacy Sandbox for full compliance with new privacy standards.
Cookieless Tracking
How to Track Performance?
Advertising performance tracking must evolve to ensure reliable and actionable measurement of campaigns. At COOL Media, we’ve developed a cookieless tracking approach based on two pillars:
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Post-Click
Post-click attribution remains fully intact thanks to the mandatory integration of our impression ID in the redirect. This mechanism ensures accurate identification of the ad source, even without third-party cookies.
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Post-View
Post-view conversion tracking relies on an advanced probabilistic model, allowing the analysis of advertising impact even when the user doesn’t click on the ad.
All pages viewed by the user, including conversion pages, are recorded through the analysis of contextual signals. Impressions are linked to conversion page visits via a probabilistic model. Modeled metrics estimate the contribution of impressions to conversions.
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