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Cookie Banners & Consent Mode: The Complete Guide for Your Website

 

In an era where online privacy is a major concern, understanding how cookie banners work is essential for any website owner. But how do you differentiate a compliant banner from an outdated one? And what exactly is Google’s Consent Mode? This guide explains everything in a simple and clear way.

 

How to Recognize a Correct and Compliant Cookie Banner

 

For years, websites used rudimentary cookie banners, often with just a simple "disclaimer" or an "OK" button. However, these banners didn't guarantee real acceptance or refusal from the user. Clicking "OK" or the "X" only closed the window, while the cookies were still saved and processed.

A cookie banner that complies with current regulations, such as GDPR, is completely different. It must offer granular control to the user, allowing them to:

• Accept all cookies: The user consents to full tracking.

• Decline all cookies: The site must "forget" this user, not saving any data.

• Accept only some cookies: The user can choose to accept, for example, technical cookies (necessary for the site's function) but decline marketing cookies.

The banner must be integrated with a detailed datalayer, which processes each user's choice and translates it into a specific action for the site and its analytics tools.

 

The Evolution of Cookie Banners: From Simple Notice to Privacy Tool

 

The old model with just an "OK" button or an "X" is now obsolete. It’s not only non-compliant with regulations, but it also fails to protect user privacy. A modern banner, on the other hand, is an interactive tool that respects the user's will by activating or deactivating specific tracking scripts based on their preferences. If a user declines marketing cookies, the site should not save or process any data related to their behavior, such as pages visited or products added to the cart.

 

 

Google Consent Mode: What It Is and Why It’s Essential

 

The introduction of Google’s Consent Mode is a crucial step for all sites that use Google Analytics, Google Ads, and other services in the suite. Consent Mode is a system that allows Google's tags to adapt their behavior based on the user's consent status. Simply put, it tells Google whether a user has agreed to the use of cookies or not.

A correct Consent Mode installation must be able to:

• Set a default denial status: Before the user provides consent, all tracking tags must be deactivated.

• Activate only the tags for which consent was given: For example, if the user accepts only analytics cookies, the system should activate only the Google Analytics tags.

 

 

 

How to Verify a Correct Consent Mode Installation

 

To see if your Consent Mode is working correctly, you can use Google Tag Manager’s preview and debugging feature. If the installation is correct, you will see the status of the tags change based on the choices made on the banner:

• Without consent: All tags should appear blocked.
• With partial or full consent: The tags corresponding to the given consent should activate.

 

 

 

Google's Data Modeling: How to Compensate for Data Loss

 

When users decline cookies, it creates a data gap that can affect analytics and marketing campaigns. To solve this problem, Google introduced data modeling.

This mechanism uses artificial intelligence and machine learning to estimate the behavior of users who did not give consent, based on the behavior of users who did accept cookies and on historical data. This way, the algorithm creates a "projection" to fill the data gap.

 

Impact on Digital Marketing and ROI

 

Data modeling is crucial for maintaining the effectiveness of marketing campaigns, such as those managed through Google's Smart Bidding. Without a modeling system, AI algorithms would see a drastic reduction in tracked users, leading to:

• Increased CPA (Cost Per Acquisition): The platform invests the same budget on a smaller number of users, making each conversion more expensive.

• Decreased ROAS (Return on Ad Spend): The return on investment appears to drop, pushing algorithms to recalibrate less efficiently.

Modeling helps overcome this "learning" phase and continues to optimize campaigns, ensuring a more accurate and complete view of user activity on the website.