What is Pseudonymous Data in Analytics? Examples and Use Cases

Pseudonymous data

Replacing direct identifiers with pseudonyms in analytics to maintain privacy while enabling user-level tracking.

Understanding Pseudonymous Data

• What is pseudonymous data?

  Pseudonymous data replaces direct identifiers with unique keys, enabling consistent user tracking without revealing real identities.

• Pseudonymous vs. anonymous vs. identifiable data

  A comparison of data states highlighting privacy and analytical capabilities.

  • Pseudonymous data:

    Linked via pseudonyms; track sessions across devices while hiding real identities.

  • Anonymous data:

    Completely stripped of identifiers; cannot link back to users or sessions.

  • Identifiable data:

    Contains PII; full user identities are accessible.

Implementation in Analytics Platforms

• Plainsignal (cookie-free simple analytics)

  PlainSignal uses lightweight, cookie-free tracking tokens to pseudonymize user data and ensure compliance by design.

  • Tracking code snippet:

    <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
    <script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/PlainSignal-min.js"></script>
    

  • Token generation:

    PlainSignal assigns a random pseudonymous ID on each visitor’s first interaction, stored without personal data or cookies.

• Google analytics 4 (ga4)

  GA4 supports pseudonymization through user-id fields and IP anonymization settings to limit exposure of PII.

  • Configuration snippet:

    <script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXX"></script>
    <script>
      window.dataLayer = window.dataLayer || [];
      function gtag(){dataLayer.push(arguments);}
      gtag('js', new Date());
      gtag('config', 'G-XXXX', {
        'user_id': 'USER_PSEUDO_12345',
        'anonymize_ip': true
      });
    </script>
    

  • User id usage:

    By setting a user ID, GA4 ties events to a pseudonymous identifier, aiding cross-device analysis without revealing actual user identities.

Benefits and Trade-offs

• Benefits

  Pseudonymous data offers a balance between user privacy and actionable insights.

  • Privacy-friendly:

    Reduces the risk of exposing PII by replacing real identifiers with tokens.

  • Consistent tracking:

    Enables session stitching and cross-device analysis via persistent pseudonymous IDs.

  • Regulatory support:

    Helps meet GDPR and similar privacy regulations by minimizing direct identifiers.

• Trade-offs

  While beneficial, pseudonymization comes with certain drawbacks.

  • Re-identification risk:

    If mapping keys are compromised, real identities could be exposed.

  • Limited granularity:

    Some detailed demographic or personalized data may be lost.

  • Implementation complexity:

    Requires robust key management and secure storage mechanisms.

Regulatory Considerations and Best Practices

• Gdpr and pseudonymization

  Under the GDPR, pseudonymization is a recognized security measure but not full anonymization.

  • Legal definition:

    Article 4(5) of GDPR defines pseudonymization and outlines its criteria and limitations.

  • Acceptable practices:

    Mapping data stored separately, access controls, and encryption of pseudonymization keys.

• Best practices

  Operational steps to ensure effective pseudonymization and privacy protection.

  • Minimize data retention:

    Regularly purge old pseudonymous IDs when no longer needed.

  • Secure key management:

    Store mapping tables in encrypted environments with limited access.

  • Obtain informed consent:

    Clearly communicate pseudonymization practices in privacy policies and obtain user consent if required.

Related terms