Web Tracking Since the EU regulation made cookie banners mandatory on many websites, the topic of web tracking has reached the broader public. Considering the complexity of the subject, along with the constant technological advancements in algorithms, data structures, and artificial intelligence, it can be assumed that general knowledge about web tracking — although it affects us all every day — remains relatively low.
Which tracking methods exist? How are they applied? How can I protect myself? Questions upon questions. To shed some light on this, the following section introduces the four most commonly used tracking methods by companies.
What is Web Tracking? Web tracking refers to the analysis of digital data traffic and is primarily used in online marketing. Synonyms such as web controlling or web analytics are also frequently used. The purpose of web tracking is to monitor and optimize entire websites as well as online marketing measures. Success and efficiency are evaluated through analysis.
Additionally, web tracking is described as a method of collecting personal data, which allows website operators to record their visitors using various tracking techniques. Based on this data, user profiles can be created, enabling targeted advertising.
The legal framework for web tracking in Germany is governed by the Telemedia Act (Telemediengesetz, TMG ), which came into effect in 2007 and represents one of the key regulations of internet law. With regard to user data, §15 (3) states that service providers may create pseudonymous user profiles for advertising or market research purposes, provided the user does not object. According to §13 (1), service providers are obligated to inform users of their right to object.
Google Analytics Now let’s look at some specific tracking methods.
Google Analytics is a free website analytics tool provided by Google, designed for traffic analysis and reporting. It tracks and evaluates visitor behavior on websites. Companies use this service in marketing to better control and measure the success of their advertising campaigns.
Key metrics offered by Google Analytics include:
Counting individual users of a website within a specific time frame (via cookies). Tracking how many pages a user visits on average and in which order. Measuring the bounce rate and calculating the average session duration. In addition, Google Analytics provides demographic insights such as age, gender, and user interests. For e-commerce businesses, the conversion rate is particularly important. This metric expresses the ratio of website visitors to actual buyers.
Beyond raw data, Google Analytics also provides clear, visual dashboards that summarize the most important results at a glance. Especially powerful is its integration with Google Ads (formerly AdWords), Google’s advertising program, which allows for highly effective synergy between advertising and analytics.
Cookies Most people have heard of cookies — and for good reason, as they are among the most common tracking methods. Cookies are small text files, only a few kilobytes in size (maximum 4KB), that are stored locally on a website visitor’s hard drive. They record user behavior, which can later be read and analyzed. Cookies also make it possible to track which advertising content a user has already seen, allowing a website to dynamically adapt to each individual visitor.
Typically, cookies serve the purpose of identification and recognition . According to current technology standards, cookies are necessary for conducting web analyses regarding visitor behavior.
There are several types of cookies:
Session cookies and persistent cookies (distinguished by validity period).First-party cookies and third-party cookies (differentiated by advertising purpose).In addition, cookies can be used to determine the number of visitors to a website within a certain timeframe, and therefore measure reach. Under the European General Data Protection Regulation (GDPR), the use of cookies is permitted only if the user provides informed consent.
Fingerprint Tracking Fingerprint tracking is considered an alternative and advanced tracking method. This technique specifically collects configuration details and system properties from consumers’ devices — most notably the IP address . It also reads browser version, browser settings and extensions, applications, operating system, and log files.
Each feature functions as an identifier, forming a unique combination that works like a digital fingerprint , allowing for user identification and recognition. When sufficiently complex, such a fingerprint is highly unlikely to appear twice.
Unlike cookies, this is a cookieless tracking method . However, the provider is legally required to inform users of its use and, where necessary, obtain consent, since personal data may be collected or at least pseudonymous user profiles may be created.
This method is particularly effective for permanent user identification and solves the problem of browsers rejecting or deleting cookies after a short time.
Logfile Analysis Finally, let’s briefly look at logfile analysis. A logfile is an automated record of all server activities. It contains detailed information about every access to a web server, such as:
the number of pages viewed, the exact time of each access, the user’s IP address, general browser data, and the session duration. Logfile analysis is considered a conventional method and the oldest technique for evaluating web server usage. It belongs to the category of server-based methods , as it uses the logfiles already available on the web server to analyze visitor activity.
In most cases, logfiles are anonymized and not linked to specific individuals, which means they generally have no relevance in terms of data protection. 1. Vgl. Berg, C. (2018), S. 57. 2. Vgl. SIT Technical Reports (2014), S. 7. 3. Vgl. BMJV (2017). 4. Vgl. Holzapfel, F. (2015), S. 176 – 179. 5. Vgl. Körner, A. (2010), S. 168 – 169. 6. Vgl. Schwarz, T. (2012), S. 236. 7. Vgl. Holzapfel, F. (2015), S. 214. 8. Vgl. Schirmbacher, M. (2017), S. 345. 9. Vgl. SIT Technical Reports (2014), S. 11. 10. Vgl. Schirmbacher, M. (2017), S. 349. 11. Vgl. Eisinger, T. (2009), S. 363. 12. Vgl. Schwarz, T. (2012), S. 236.