Published on 2025-06-22T10:10:11Z

What is User Matching? Examples in PlainSignal and GA4

User Matching in web analytics refers to the process of identifying and linking interactions from the same user across multiple sessions, devices, or touchpoints. It enables analysts to understand user behavior holistically, rather than as isolated visits.

Techniques range from traditional cookie-based methods—where a unique client ID stored in a cookie ties sessions together—to more modern, cookieless approaches like those used by PlainSignal, which relies on device fingerprints and probabilistic signals. Google Analytics 4 (GA4) offers both client ID and a configurable userID parameter, allowing deterministic matching when users authenticate.

Effective user matching helps in building accurate user journeys, personalization strategies, and recurring visitor metrics, but it must be balanced against privacy regulations such as GDPR and CCPA. In this article, we explore the methods, real-world implementations, and best practices for user matching in PlainSignal and GA4.

Illustration of User matching
Illustration of User matching

User matching

Mapping interactions from the same individual across sessions and devices using identifiers in analytics tools like PlainSignal and GA4.

Introduction to User Matching

User matching is the practice of associating web interactions from the same person across different sessions and devices. By recognizing repeat visitors and merging their behavior into unified user profiles, analysts gain deeper insights into customer journeys, retention, and conversion metrics.

  • Definition

    Identifying and linking multiple interactions as belonging to one user, rather than treating each visit in isolation.

  • Goals

    Improve data accuracy, enable personalized experiences, and measure true user engagement over time.

Methods of User Matching

Various techniques can be employed to match users. Each method involves trade-offs between accuracy, persistence, and privacy.

  • Cookie-based matching

    Uses browser cookies to store a unique client identifier. Works well for tracking sessions on the same device and browser.

    • First-party cookies:

      Set by your own domain; generally more reliable and privacy-friendly than third-party cookies.

    • Third-party cookies:

      Set by external domains; increasingly blocked by modern browsers and privacy regulations.

  • Device fingerprinting

    Combines attributes like browser version, screen resolution, and OS to probabilistically recognize returning devices without cookies.

  • Deterministic vs probabilistic matching

    Deterministic matching uses exact identifiers (e.g., user IDs), while probabilistic matching relies on statistical algorithms to infer identity.

Implementing User Matching with PlainSignal

PlainSignal offers a cookieless analytics solution that leverages probabilistic signals to approximate user matching, reducing reliance on persistent cookies while maintaining user privacy.

  • Installation

    Add the following snippet to your site to initialize PlainSignal:

    • Code example: 
      <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>

  • Configuration

    Use the data-id attribute to specify your PlainSignal project ID (e.g., 0GQV1xmtzQQ). You can also customize event naming and API endpoints via data attributes.

  • Limitations

    Cookieless matching may have lower cross-session persistence than deterministic methods and can be affected by browser privacy features.

Implementing User Matching with GA4

Google Analytics 4 uses both client-side cookies and optional user IDs to achieve user matching across sessions and devices.

  • Client id

    Automatically generated by GA4 (_ga cookie) to identify unique browsing sessions on a single device.

  • User id

    A custom, deterministic identifier that you can set when users log in, enabling cross-device session stitching.

  • Gtag implementation

    Example of sending a user_id with GA4 configuration:

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

Best Practices and Challenges

Effective user matching requires balancing accuracy, user privacy, and regulatory compliance. Consider the following when designing your matching strategy.

  • Privacy compliance

    Implement consent management frameworks and anonymization to align with GDPR, CCPA, and other regulations.

  • Data accuracy

    Be consistent with identifier strategies to avoid fragmented or duplicate user profiles.

  • Cross-device tracking

    Encourage authenticated logins for deterministic matching; otherwise, rely on probabilistic methods with clear transparency.

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