Error Rate
Error rate measures the proportion of user interactions, API calls, or system events that result in an error. For product teams, it's a leading indicator of user experience quality — rising error rates precede churn and support volume spikes. For engineering teams, it's a primary SLI (Service Level Indicator) within SLOs. Tracking error rate by feature, endpoint, and user segment enables fast, targeted remediation.
Note: Track separately: client-side errors (JS exceptions, crashes), server-side errors (5xx responses), and business logic errors (invalid state transitions). They have different causes and different impact on users.
API error rate < 0.1% (99.9% success rate); critical path error rate < 0.01%
Error rate > 1% on core user flows will measurably increase churn and support volume
Benchmarks by segment
How to improve Error Rate
Set up real-time error alerting with severity tiers — P0/P1 errors page on-call; P2/P3 go into a triage queue
Build error budgets: define an acceptable monthly error budget per endpoint; when the budget is exhausted, stop new feature work and fix reliability
Add structured error logging so every error is tagged with user segment, feature, and environment — makes root-cause analysis 10× faster
Run chaos engineering (controlled fault injection) to find reliability weaknesses before users do
Common measurement mistakes
Tools for measuring Error Rate
Best-in-class behavioral analytics with powerful event segmentation, funnel analysis, and retention charts that go far deeper than Google Analytics
Best-in-class event-based analytics with intuitive funnel, retention, and flow reports that surface actionable insights quickly
Best-in-class autocapture technology — captures every click, scroll, and interaction without manual event tagging, enabling retroactive analysis on historical data
All-in-one product analytics platform combining analytics, session replay, feature flags, A/B testing, surveys, and a data warehouse — replacing multiple point solutions
Autocapture eliminates the need for manual event instrumentation — every click, pageview, and form interaction is tracked automatically from day one
All-in-one platform combining feature flags, A/B testing, product analytics, session replay, and web analytics — eliminating the need for separate tools
Frequently Asked Questions
An error budget is the maximum acceptable error rate for a service over a rolling window (typically 30 days). If your SLO is 99.9% success rate, your error budget is 0.1% — that's 43.8 minutes of downtime or errors per month. When the budget is consumed, reliability work takes priority over new features.
Use severity tiering and deduplication. Group repeated identical errors into a single alert. Set minimum thresholds (e.g. only alert if > 10 errors in 5 minutes). Tools like Sentry, Datadog, and Rollbar handle this automatically.