Error tracking helps you find and fix problems in your analytics implementation. When data collection breaks, error tracking tells you exactly what went wrong and where. This is different from data validation — it focuses on technical failures like tracking code errors, API timeouts, or integration problems.

Common error tracking includes failed API calls, JavaScript errors, and data pipeline failures. Tools like Sentry and Datadog can catch these issues automatically. For example, they'll alert you if your analytics tags stop firing, if there are JavaScript errors in your tracking code, or if your data warehouse ingestion fails.

Set up alerts for different error types based on their severity. Critical errors (like complete tracking failure) need immediate attention, while minor issues (like occasional timeouts) can be reviewed daily. Group similar errors together to spot patterns — like tracking breaks after specific types of code deployments.