Pseudonymization: Server-side tracking with Data Protection

The JENTIS Server-side Tracking Platform offers the ability to pseudonymise data streams for your analytics and marketing tools, allowing you to select which tools receive pseudonymized data. This enables customized data processing that meets your company’s requirements while ensuring compliance with GDPR regulations. By providing precise control over data management, JENTIS allows website operators to maintain the highest level of data protection, avoiding the legal uncertainties of international data transfers while still enabling effective use and interpretation of the data.

Pseudonymisation and anonymisation are essential techniques for marketers to conduct data-driven campaigns that are both compliant with data protection regulations and effective. While pseudonymisation enables secure data processing by replacing personal identifiers with pseudonyms, anonymisation ensures that no inferences can be made about individuals. These techniques not only offer enhanced data protection and compliance but also provide the opportunity to conduct valuable market research and targeted campaigns without compromising customer privacy. Discover how these methods can strengthen your marketing strategy.

What is Pseudonymisation?

Pseudonymisation is a process in which personal IDs within datasets are replaced with artificial IDs or pseudonyms. This method makes it significantly more difficult to trace data back to specific individuals, thereby greatly reducing the risk of data breaches or misuse. Pseudonymous IDs are randomly generated and can only be traced back to the individual through a separate, securely stored key.

Relevance of Pseudonymisation in the GDPR

The GDPR defines pseudonymisation in Article 4(5) as “the processing of personal data in such a way that the personal data can no longer be attributed to a specific data subject without the use of additional information.” This additional information must be kept separately and be subject to technical and organisational measures to ensure that the personal data cannot be attributed to an identifiable natural person.

For companies, this means that they can still associate the collected data with an individual through pseudonymisation, while analytics and marketing tool providers, to whom this data is forwarded, cannot draw conclusions about the person’s identity. This preserves data protection, and tools like Google Analytics 4 can continue to be used as usual.

Anonymisation: An Overview

Anonymisation is a process that alters personal data so that the individual concerned is no longer identifiable. In contrast to pseudonymisation, where data can be traced back to a person using a separate key, anonymisation makes any identification impossible.

The Role of Anonymisation in the GDPR

According to Article 89(1) of the GDPR, anonymised data is no longer considered personal data. This means that anonymised data is not subject to the same strict data protection regulations as personal data. This is a significant relief for companies that process large amounts of data, as anonymisation allows data to be used without falling under the full requirements of the GDPR.

However, it is important to note that anonymisation can be challenging to implement in practice, especially with complex datasets. There is always a risk that seemingly anonymised data can be re-identified by cross-referencing with other datasets. Therefore, anonymisation requires careful planning and execution to ensure that the data remains truly anonymous.

Methods of Anonymisation

Various techniques can be used to anonymise data, including:

• Suppression: Removing identifiers such as names, addresses, or phone numbers.
• Masking: Altering data values, such as replacing birthdates with age ranges.
• Generalisation: Replacing specific data with broader categories, e.g., “Berlin” with “Germany.”
• Data Randomisation: Randomly altering data to obscure individual identifiers.
• Differential Privacy: Adding noise to the data to prevent inferences about individuals.

Practical Examples of Anonymisation

A common example of anonymisation is the removal of patient names and addresses from medical datasets used for research purposes. In market research, personal data is often anonymised to analyse trends without compromising the participants’ privacy.

Another example is the anonymisation of data for statistical analyses. Companies can anonymise customer data to identify patterns and trends without violating data protection regulations.

Challenges and Limitations of Anonymisation

Complete anonymisation of data is often difficult to achieve in practice, particularly with large and complex datasets. Even if identifying information is removed, other remaining data points combined with external data sources can potentially lead to re-identification. This is known as “collateral re-identification” and poses a significant risk.

To minimise this risk, anonymisation must be carefully planned and regularly reviewed. Companies should also consider whether a combination of anonymisation and pseudonymisation is advisable to ensure the best possible data protection.

Anonymisation vs. Pseudonymisation: Which is Better?

Whether anonymisation or pseudonymisation is the better choice depends on the specific needs of the company. Anonymisation is ideal when data needs to be completely separated from personal information, and no traceability back to the individual is required. This is particularly useful for statistical analyses or scientific research.

Pseudonymisation, on the other hand, is better suited when it is necessary to continue associating the data with an individual, whether for personalised marketing strategies or detailed analyses. Pseudonymisation offers higher data protection than direct storage of personal data but remains under the strict requirements of the GDPR.

Pseudonymisation and Anonymisation in Server-Side Tracking

With server-side tracking, companies have full control over their data collection and processing. This allows for targeted application of pseudonymisation and anonymisation to ensure the protection of personal data. The flexible architecture of JENTIS allows data points to be processed individually before being forwarded to third-party tools. This means that companies can decide whether data should be pseudonymised or anonymised depending on their needs and in compliance with relevant data protection requirements. By applying these techniques precisely and individually, companies can control their data processing while ensuring compliance with data protection regulations.

Advantages of Pseudonymisation in Server-Side Tracking

Integrating pseudonymisation with server-side tracking offers several key benefits:

• Increased Data Protection: Pseudonymisation significantly reduces the risks of data breaches and misuse.
• GDPR Compliance: Companies can continue to process and analyse data without violating data protection regulations. Article 32 of the GDPR requires companies to implement appropriate technical and organisational measures to ensure a level of security appropriate to the risk. Pseudonymisation is one such measure.
• Customer Satisfaction and Trust: By adhering to data protection regulations, companies strengthen customer trust and promote engagement.
• Flexibility in Data Processing: Pseudonymisation allows for detailed data analysis and personalised marketing strategies without violating strict data protection requirements.
• Simplification of International Data Transfers: By processing and pseudonymising data locally, compliance risks in international data transfers can be minimised. Articles 44-50 of the GDPR govern international data transfers and emphasise the need for an adequate level of protection, which pseudonymisation can support.

Importance of Pseudonymisation for Marketers

In today’s data-driven marketing landscape, both pseudonymisation and anonymisation are crucial to ensuring legal compliance while executing effective campaigns. Integrating pseudonymisation with server-side tracking offers several key benefits for marketers:

• Improved Data Protection Compliance in Campaigns: By applying pseudonymisation, companies can continue to run personalised marketing campaigns without violating data protection regulations. As user identities are protected by pseudonyms, personalised content and targeted advertising can be delivered based on pseudonymised data. This allows for individual customer engagement without compromising their privacy.
• Increased Customer Retention and Trust: Customers are increasingly concerned about the protection of their personal data. By implementing pseudonymisation and anonymisation techniques, companies can demonstrate that they take their customers’ privacy seriously. This strengthens trust and promotes customer loyalty, as consumers can be confident that their data is being processed securely.
• Use of Anonymised Data for Market Research: Anonymised data is highly valuable for market research, as it allows companies to conduct comprehensive analyses without revealing the identity of participants. By analysing anonymised data, trends can be identified, target groups better understood, and new market opportunities uncovered, all while ensuring GDPR compliance.
• More Efficient Target Group Segmentation: Pseudonymisation can also help segment target groups more accurately without the risk of data protection violations. Companies can use pseudonymised data to create customer profiles and tailor marketing messages to specific demographic groups, leading to more effective campaigns and higher success rates.
• Reduced Risks in International Marketing Activities: International marketing campaigns are often subject to strict data protection regulations, particularly when transferring data to countries outside the EU. Pseudonymisation and anonymisation offer a way to mitigate these risks by ensuring that personal data is protected even during cross-border transfers. This enables companies to operate globally without violating data protection laws.

Practical Examples of Pseudonymisation

• Example 1: A retail company anonymises sales data to analyse which products are particularly in demand at certain times of the year. All personal identifiers are removed, so the data does not allow any conclusions to be drawn about individual customers. The company can still identify trends or determine which promotions are most effective. The analysis of anonymised data allows informed business decisions to be made while ensuring GDPR compliance.
• Example 2: An online shop uses pseudonymised IDs instead of real customer data when conducting targeted email campaigns. Pseudonymisation replaces personal identifiers such as names or email addresses with randomly generated codes. These codes allow personalised offers to be sent to customers while keeping the direct connection to their real identities hidden. Particularly when using third-party tools for campaign management, it is important that they only have access to pseudonymised data to protect customer privacy.

Conclusion: Pseudonymisation and Anonymisation as Keys to GDPR Compliance

Both pseudonymisation and anonymisation are essential tools for handling personal data in compliance with data protection regulations. With the JENTIS Data Capture Platform, companies can manage their data streams securely and effectively without violating GDPR requirements. This enables them to gain valuable insights while simultaneously strengthening customer trust in data protection. While anonymisation offers the highest level of protection by preventing any identification, pseudonymisation enables flexible data processing that meets both data protection requirements and business needs.

JENTIS Essential Mode

For companies looking to further optimize their data protection strategies, JENTIS Essential Mode offers a specially developed solution that provides even more control and flexibility in data processing. This functionality helps companies manage their data streams more efficiently while maintaining the highest data protection standards. JENTIS Essential Mode combines the benefits of pseudonymization with advanced server-side tracking features to ensure an even better adaptation to individual data protection requirements.

For more information on the features and benefits of JENTIS Essential Mode, click here.