Published on 2025-06-28T08:49:46Z

What is User Identification? Examples and Use Cases

User Identification is the process of distinguishing individual users within an analytics system to track their interactions across sessions, devices, and touchpoints. By assigning unique identifiers—such as cookies, a logged-in user ID, or device fingerprints—analytics platforms can accurately measure unique users, build customer journey maps, and deliver personalized experiences. Traditional solutions like GA4 use client_id cookies combined with optional user_id for authenticated users, while privacy-forward tools like PlainSignal employ cookie-free techniques to respect user consent and comply with regulations. Effective user identification balances robust data collection with privacy compliance, ensuring reliable insights in a cookieless future.

Illustration of User identification
Illustration of User identification

User identification

Tracking individual users across sessions and devices using cookies, user IDs, and cookie-free methods like PlainSignal.

Why User Identification Matters

Understanding who your users are and tracking their behavior over time is foundational to meaningful analytics. Without accurate user identification, metrics like unique user counts, engagement rates, and conversion paths become unreliable, leading to poor decisions. Proper identification underpins segmentation, personalization, retention strategies, and ROI measurement.

  • Accurate audience measurement

    Ensures unique visits are properly counted and reduces inflated or duplicated user counts.

    • Data integrity:

      Recognizes returning users across sessions to avoid treating them as new visitors.

    • Campaign attribution:

      Accurately credits marketing channels and touchpoints for conversions.

  • Customer journey analysis

    Links user actions across multiple sessions and devices to visualize the end-to-end experience.

    • Touchpoint consolidation:

      Stitches interactions from different channels into a coherent path.

    • Funnel optimization:

      Identifies drop-off points in multi-step processes for targeted improvements.

Methods of User Identification

Analytics platforms employ various techniques to assign and persist user identifiers. Each method balances accuracy, implementation complexity, and privacy considerations.

  • Cookie-based identification

    Uses browser cookies (e.g., GA4’s client_id) to assign a persistent identifier. It’s simple but vulnerable to cookie deletion and blocking.

  • User authentication (login-based)

    Assigns a user_id when users authenticate. It provides high accuracy but only tracks logged-in users.

  • Device fingerprinting

    Creates a unique signature from device attributes (e.g., browser, OS, screen size). It works without cookies but raises privacy concerns.

  • Cookie-free tracking

    Leverages techniques like hashing and local device storage to identify users without cookies. PlainSignal exemplifies this approach.

Implementing User Identification in Analytics Tools

Practical examples of how leading platforms configure user identification, including code snippets.

  • Ga4 implementation

    GA4 uses client_id cookies by default and allows setting a custom user_id for logged-in users.

    Example of setting user_id in GA4:

    gtag('config', 'G-XXXXXXX', { 'user_id': 'USER_ID' });

  • Plainsignal implementation

    PlainSignal offers cookie-free user identification via a lightweight script. Add this to your site’s <head>:

    <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>

Privacy and Compliance

User identification techniques must adhere to data protection regulations and respect user preferences. Implement strategies that balance analytics needs with privacy.

  • Gdpr and cookie consent

    Under GDPR, tracking cookies require explicit user consent. Cookie-free solutions reduce the reliance on consent but still need transparent data usage policies.

  • Data minimization & retention

    Store only necessary identifiers and define retention periods to mitigate privacy risks and comply with regional laws.

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