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Cookieless Analytics Guide

Cookie measurement is a technique used in web analytics and digital advertising to track and collect data about user behavior on the Internet. A cookie is a small text file that a website sends to the user’s browser. This file is stored on the user’s device and contains information that can be read by the web server on future visits.

How does Cookie-based Measurement Work?

Creating and Storing Cookies:

When a user visits a website for the first time, the site creates a cookie and stores it on the user’s browser.

This cookie contains a unique identifier that represents the user.

Tracking and Data Collection:

Each time the user visits the website or interacts with an advertisement, the cookie sends information to the server.

This information may include details such as length of visit, pages viewed, clicks on specific links, and actions taken on the site.

Data Analysis:

The data collected is used to analyze user behavior, such as browsing patterns, preferences and interaction with content or advertisements.

This data helps websites and advertisers improve the user experience, personalize content and ads, and measure the effectiveness of advertising campaigns.

Personalization and Targeted Advertising:

Based on the information collected, websites can personalize the user experience and advertisers can target specific ads that match the user’s interests.

Cookie measurement has been central to the development of online advertising and web analytics, but has also raised concerns about privacy and user consent, leading to increased interest in alternative measurement methods, such as cookie-free solutions.

Issues with Cookie-based Measurement

Measurement with cookies, while it has been a standard in web analytics and digital advertising, presents several issues related to technical and privacy issues and other challenges. Here are some of them:

Technical Issues

Cookie Blocking:

Many browsers and privacy extensions block third-party cookies, which prevents advertisers and websites from effectively tracking users.

Cookie Blocking can also affect the accuracy of conversion measurement and visitor tracking.

Limitations on Mobile Devices:

Cookies do not work in a uniform manner on mobile devices, which can lead to inconsistent and less accurate data collection.

Browser Dependency:

Cookies are tied to the browser used by the user, so they do not allow for effective tracking across different devices or browsers.

Privacy Issues

User Consent:

Privacy laws such as GDPR and CCPA require websites to obtain consent from users before using cookies, which can limit the amount of data collected.

Many users choose not to consent to the use of cookies, which reduces the effectiveness of this methodology.

Privacy Concerns:

The use of cookies to track user behavior online has raised concerns about privacy and misuse of personal data.

Transparency and user control over their own data are becoming increasingly important issues.

Other Challenges

Adoption of Privacy-Oriented Browsers:

The rise in popularity of browsers that prioritize privacy and automatically block cookies makes data collection even more difficult.

Data Fragmentation:

Cookie-based measurement can result in a fragmented view of the user, as data is separated by session and device, making a unified view of user behavior difficult.

Dependence on Third-Party Policies:

Privacy policies and technology changes driven by big players such as Google and Apple can significantly affect the effectiveness of cookies.

These issues have led to a growing interest in alternative measurement methods, such as cookie-free solutions, that seek to balance the need to collect data for analytics and advertising while respecting user privacy.

How Cookie-based Measurement Issues Affect Data Quality

Issues associated with cookie-based measurement can have a significant impact on several key web analytics metrics. This impact includes:

Increased Direct Traffic

Inaccurate Traffic Attribution:

Cookie Blocking makes it difficult to attribute traffic sources correctly. For example, if cookies do not adequately track where users come from, many visitors may be mistakenly categorized as direct traffic.

This leads to an overestimation of direct traffic, leading to misinformed marketing decisions.

Increased Bounce Rate

Incomplete Tracking of User Sessions:

Without effective cookie tracking, it can be challenging to determine if a user interacts with multiple pages or leaves the site after the first page.

This can result in an artificially high bounce rate, as sessions that are not correctly tracked may appear to be single-page visits.

Decrease in Page Views per Session

Difficulty in Tracking User Navigation:

If cookies are blocked or deleted, tracking user navigation across different pages becomes more challenging.

This can lead to an incorrect record of page views, giving the impression that users view fewer pages per session than they do.

Other Impacts

Conversion Tracking Challenges:

Conversion measurement can be impacted as cookies are often essential to track the user journey from a click on an ad to a conversion action (such as a purchase or registration).

Lack of accurate tracking can underestimate conversions, affecting the ROI evaluation of ad campaigns.

Inaccurate Audience Data:

Without reliable cookie tracking, user demographics and interest data can be less accurate, affecting the ability to segment and target specific audiences.

In short, problems with cookie-based measurement can lead to an incomplete and sometimes misleading understanding of user behavior, affecting decision-making in digital marketing, content optimization and advertising strategies.

Introduction to Cookieless Analytics

Cookieless Analytics refers to web analytics techniques and tools that do not rely on using cookies to track and collect data on user behavior. These techniques are becoming increasingly important due to growing concerns about online privacy and changes in legislation and technology.

In the current context, where data privacy is a priority for both users and regulators, Cookieless Analytics offers an alternative that respects user privacy.

With increasing restrictions on third-party cookies and stricter privacy policies, such as GDPR in Europe and CCPA in California, Cookieless Analytics technology is becoming a necessity for online businesses.

Cookieless Analytics Fundamentals

Cookieless Analytics involves collecting and analyzing user data on a website or application without using cookies, i.e., without relying on small text files stored on the user’s device. This measurement form uses alternatives that respect user privacy and comply with data protection regulations.

Main differences between Cookieless Analytics and Cookie-based measurement:

Aspect

With Cookies

Without Cookies

Data Collection Method

Based on storing and retrieving information from the user’s device.

It uses techniques like HTML5 local storage, digital fingerprinting or server-generated tokens.

Privacy and Consent

Requires explicit user consent, especially under regulations such as GDPR.

Designed to minimize the collection of personal data and operate within a stricter legal framework.

Persistence and Accuracy

Allows for more persistent and personalized tracking but may be less accurate due to cookie blocking.

Provides an overview of user behavior, but with limitations on personalization and persistence of tracking.

Importance of Privacy and Regulatory Compliance (GDPR, CCPA, etc.)

Legal Compliance: Cookieless Analytics is designed to comply with privacy laws such as GDPR in Europe and CCPA in California, which impose strict restrictions on the use of personal data.

Respect for User Privacy: These techniques respond to the growing demand for greater online privacy, giving users more control over their data.

Adjustment to Technological Changes: The trend towards the elimination of third-party cookies by technology giants such as Google and Apple makes Cookieless Analytics increasingly relevant.

Cookieless measurement methods

Anonymous Identifier Based Measurement

Description: Uses unique identifiers that do not contain personally identifiable information. These identifiers allow tracking user activity on a website without revealing their identity.

How it works: Each user receives a unique ID when visiting a website. This ID is used to track their behavior on the site, but is not linked to personal data.

Advantages: Allows a certain level of individualized tracking while respecting the user’s privacy.

Use of HTML% Local Storage

Description: HTML5 local storage allows websites to store data in the user’s browser more flexibly and with greater capacity than traditional cookies.

How it works: Data is stored directly in the user’s browser and can be used to track preferences and behaviors without relying on cookies.

Advantages: More difficult to block than traditional cookies and allows a larger amount of data to be stored.

Digital Fingerprints

Fingerprinting is a web analytics technique that identifies unique devices or browsers without the need for cookies. Unlike cookies, which store information on the user’s device, fingerprinting collects data from the device to create a unique profile.

How does it work?

Data Collection:

Fingerprinting collects information about the user’s device, such as browser type, operating system, language setting, screen resolution and other device settings.

Creation of a Unique Fingerprint: This data is combined to create a unique “fingerprint” of that device or browser.

Identification and Tracking: This fingerprint allows web analysts to identify and track user behavior on the website without the need for cookies.

As you can see in the explanation, although they do not use cookies, since all analytics happens on the analytics solution’s server, the action of individually measuring a user requires consent.

To better understand the concept of fingerprinting vs. cookies: Fingerprinting creates an ID of a user, which can be anonymous, and measures everything that user does. There are tools that erase this ID after 24h, 12h, 1h,… A cookie creates a user ID, which can be anonymous, but is stored on the user’s computer, and measures all the user’s behavior. The cookie can have a duration of 24h, 1h, or as long as the session lasts.

Regulations state two important things:

You can’t put anything on the user’s computer without their consent. If you measure individually, it requires consent.

If we go back to the fingerprinting vs cookies comparison, you will see that they act the same in terms of measuring users. So measuring with fingerprinting requires consent.

First-Party Identifiers

Description: Uses identifiers created and stored by the website itself (first-party), rather than third parties, to track user activity.

How it works: For example, SEALMetrics uses a Source-ID that identifies the source, campaign, term and medium, but is not associated with the individual user.

Advantages: Fully under the control of the website owner and in compliance with privacy regulations.



Cookieless measurement method


Consent Required (Yes/No)


Reason for Consent Requirement or No Consent Requirement



Anonymous Identifier Based Measurement



Yes


If measured individually, even anonymously, it requires consent.



Use of Local Storage



Yes


If any code is added to the user’s terminal, consent is required.



Digital Fingerprints



Yes


If measured individually, even anonymously, it requires consent.



First-Party Identifiers (Example: Source-ID in SEALMetrics)





No


Identifiers are generated and used internally by the website, without tracking personal user data or individual users. Users are NOT identifiable or identified.

Therefore, as you can see in the table, measuring with cookies and with other technology than First-Party Identifiers would require consent.

The reason is because both work with user or session IDs. So you are measuring a user individually even if it is anonymously.

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