Professor Arvind Narayanan (Princeton University, New Jersey, USA) sees the "arms race between trackers and data protection officers" as an attempt of companies to make the online behavior of prospects and customers transparent and usable for marketing purposes. Professor Narayanan uses bots to scan a million important websites every month for tracking and other monitoring methods. It emerges that despite improved data protection, the tracking takes place with continuously refined methods in order to gain insights into surfing behavior.

It is in the interest of many companies to understand the behavior of users of their online platforms. And this seems quite justified: The observation of the users forms an important basis in order to be able to improve the offer and usability of services and interfaces. This optimization process increases the competitiveness of the company on the one hand, but also benefits the consumer on the other hand - because its surfing behavior means that customized and individual page content and communication can be compiled automatically.

On the other hand, three quarters of German Internet users care much about privacy and are very concerned that they have no insight into what happens to the recorded data. This is the result of a study by the University of Hohenheim. The majority of respondents also fear that the personal data will fall into unknown hands.

There is a wide range of methods of tracking a user's path on a website or across multiple websites or when using an online application and reading out typical user characteristics. Which tracking method or combination of methods you choose depends essentially on the analysis goals, because each tracking method has specific advantages and disadvantages.

A modern alternative to cookie tracking is to recognize a user by certain software and hardware features. When a page is loaded in the browser, data is automatically transferred to the provider's system. Since there are tens of thousands of program and system components, the individual configuration of the user or of his device results in a distinctive 'fingerprint'. With the recording of the system data of the user, one can assume that the user is clearly identified. The advantage of this method compared to online tracking via cookies is obvious: Even if the user deletes or suppresses cookies, fingerprinting still works because the fingerprint information is stored on the provider's server and not on the user's computer.

For all web content that requires registration and can only be accessed via a login, the simplest method of tracking is to track the 'Common-ID': When registering, each user receives a unique identification number that will later be uniquely identified and tracked. Tracking with common ID is e.g. used for Google services (mail, drive, etc.). The user can of course only be tracked as long as he is logged in to a website that uses common IDs.

Database tracking is one of the newer tracking methods in the special case of 'affiliate marketing'. With database tracking, the affiliate partner's ID is generated and saved either from the URL or from the cookie together with the respective customer ID, so that not only individual transactions of the user but also subsequent transactions can be assigned. This method enables the provider to pay his affiliate partner not only the immediate but also the future transactions. The consideration of follow-up transactions is often used for 'lifetime commissions', since the identification of the user with the saved customer data including the partner ID is particularly meaningful for further analyzes (e.g. on the purchase behavior or the purchase volume). A disadvantage of this tracking method lies in the unequal treatment of affiliates, since new intermediaries are not remunerated for the transmission of customers if the customer is already stored in the database via another affiliate partner with their partner ID.

The pixel tracking method is often used when a success, e.g. a conversion shall be measured. This method is for example used by Facebook. A tracking pixel (1 × 1 pixel image in GIF format) is stored on the website in the HTML code of the page, which notifies the page provider (or in social networks the network operator) of a successful conversion. The tracking pixel sends information such as 'form has been sent', 'revenue has been generated' or 'percentage commission is due' to the website operator. Pixel tracking is often combined with cookie tracking in affiliate marketing. Tracking works very reliably and can only be prevented by the website visitor deactivating the display of images in his browser.

When visiting a page, the user is assigned an eTag (unique ID) in the browser cache. The eTag is saved in the cache of all new page visitors, for whom no previously stored eTag is found. These 'cookieless cookies' cannot be overridden by blocking JavaScript or by refusing cookies. When the browser cache is switched off and the browser cache is cleared, however, they will be blocked or deleted.

Affiliate marketing uses other (sub)forms of tracking. These include 'Postview Tracking', 'Flash Cookie Tracking' and a few others, we would be happy to advise you on their uses and advantages.

"Knowledge is power" - this is particularly relevant when evaluating the data collected through online tracking. Certainly, the careful handling of data, data security and data economy are of particular importance today. But with a competently created strategy and a well-designed analysis, you can derive valid recommendations for action from almost any market and company situation.

"Time is money" - this applies particularly to personnel-intensive services. It is therefore not surprising that companies automate work processes as much as possible (either on their own initiative or by force). Large, often untapped potential still lies in automation or resource optimization for marketing tasks. At this point, the use of appropriate online tracking can not only save some work, but above all it can help to fully objectify 'felt' evaluations of data.

In the 'frontend' - i.e. in the web application - the spectrum of tracking applications ranges from the analysis of the web interface for usability and momentum to the display of individually compiled page content. Professionalization in automated communication (right down to AI) also builds on the recognition of a visitors and their concerns.

With a skillful evaluation of the tracked data, it is not only possible to re-provide shopping carts or forms that have not been sent, but e.g. also to decide in principle whether the user should use discounts, vouchers, notifications by email, telephone or e.g. can better be motivated by the personal visit of a sales employee.

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