Measurement

Error Rate

A UX metric for understanding how often defined user errors occur during a task or journey.

Concept facts

Error rate records how often users make defined errors while attempting a task or journey under evaluation conditions.

Also known as
Mistake rate, user errors, task errors.
Used in
Usability testing, form review, transaction evaluation, accessibility checks, and service-quality analysis.
Interpret with
Task success, time on task, severity, recovery effort, accessibility barriers, and error-prevention design.

Plain-language explanation

An error is an action, omission, or misunderstanding that deviates from the defined successful task outcome. Error rate helps teams see whether problems are occasional, repeated, severe, or tied to a specific interface pattern.

The team must define what counts as an error before analysis. A typo, skipped required field, wrong service selection, repeated failed search, or incorrect upload may not have the same impact.

Why it matters

Errors can create service failure even when a user eventually reaches the final screen. In banking, health, telecom, education, and public-service journeys, an error may affect eligibility, payment, access, trust, or safety.

Use contexts

  • Complex forms and eligibility checks.
  • Payment, account, and transaction flows.
  • Service applications and document uploads.
  • Navigation and search tasks.

Application guidance

Define error categories, record severity, note whether users recover, and separate user mistakes from system or content conditions that made the mistake likely.

Practical example

A mobile financial service introduces a KYC update flow requiring users to re-enter national identity information and confirm account ownership.

During evaluation, many users submit the wrong date format or mismatch the ID number with the account holder’s name. The error rate is not only a form-quality issue; it indicates risk of failed verification, account restriction, support-center load, and exclusion of users with low digital confidence.

Interpretive boundaries

  • Error rate depends on how errors are defined.
  • Not every error has the same severity.
  • Error rate does not explain cause by itself.
  • Some errors are prevented through better content, validation, feedback, or accessibility support.

Applied at Userhub

Error rate can help Userhub evaluate whether important digital-service journeys are creating avoidable mistakes in forms, portals, applications, and transactional flows.

See Userhub UX Lab for applied UX research and evaluation context.

Sources and references

  • ISO. (2018). Ergonomics of human-system interaction – Part 11: Usability: Definitions and concepts (ISO Standard No. 9241-11:2018). International Organization for Standardization.
  • Reason, J. (1990). Human Error. Cambridge University Press.
  • Reason, J. (2000). Human error: Models and management. BMJ, 320(7237), 768-770. https://doi.org/10.1136/bmj.320.7237.768
  • Norman, D. A. (2013). The Design of Everyday Things (Revised and expanded ed.). Basic Books.

Cite this entry

APA

Userhub. (2026). Error Rate. UX Reference. https://userhub.com.bd/reference/error-rate/