What is Error Tracking? Examples of Error Tracking in Analytics

Error tracking

Error Tracking captures and analyzes application errors to improve performance, user experience, and system reliability.

Why Error Tracking Matters

• User experience impact

  Errors disrupt the user journey, leading to frustration and potential churn. Tracking errors helps identify pain points and prioritize fixes that improve usability.

• Business and revenue implications

  Critical errors can result in lost revenue, tarnish brand reputation, and increase support costs. Proactive error monitoring minimizes these risks.

• Operational efficiency

  Error Tracking reduces the time spent debugging by providing contextual information and stack traces, enabling faster resolution.

How Error Tracking Works

• Client-side vs server-side tracking

  Client-side tracking catches errors in user browsers (JavaScript), while server-side captures backend exceptions. Both are necessary for comprehensive monitoring.

  • Client-side:

    Monitors errors like JavaScript exceptions, resource loading failures, and API response errors in real time.

  • Server-side:

    Logs uncaught exceptions, crashes, and performance bottlenecks on the server to backend error tracking services.

• Key components

  Effective error tracking consists of error capture, aggregation, deduplication, contextual data (user, device, environment), and alerting.

  • Error capture:

    Hooks into exception handlers or uses global listeners to catch errors automatically.

  • Aggregation & deduplication:

    Groups similar errors to reduce noise and prevent alert fatigue.

  • Contextual data:

    Includes user IDs, browser versions, stack traces, and custom metadata for faster debugging.

Error Tracking with SaaS Tools

• Plainsignal (cookie-free simple analytics)

  Primarily an analytics tool, PlainSignal can be extended for error tracking by capturing client-side errors alongside user behavior without cookies.

  • Integration example:

    Use the PlainSignal script to capture errors and events with custom API endpoints.

  • Sample tracking code:

    <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>
    

• Ga4 (google analytics 4)

  GA4 supports enhanced measurement for web errors by sending custom events when exceptions occur.

  • Setup steps:

    Configure GA4 to capture exception events via gtag or Google Tag Manager.

  • Event example:

    gtag('event', 'exception', {
      description: 'TypeError: undefined is not a function',
      fatal: false
    });
    

Best Practices for Error Tracking

• Define severity levels

  Classify errors by impact (Critical, High, Medium, Low) to prioritize responses.

• Implement rate limiting

  Prevent flooding your dashboard with repeated errors from mass issues by limiting event frequency.

• Enrich with context

  Attach user IDs, session data, and environment details to each error report for quicker resolution.

Troubleshooting Common Issues

• Missing error reports

  Check that your scripts are loaded and error handlers are correctly initialized before other scripts.

• High volume noise

  Use sampling, filters, and grouping to reduce duplicate or low-priority error reports.

• Privacy compliance

  Ensure no sensitive data (PII) is sent in error payloads. Use hashing or anonymization if needed.

Related terms