AI EvaluationHow to Set Up Scoring Labels

How to Set Up Scoring Labels

Configure scoring labels to map candidate score ranges to performance levels and filter candidates by overall assessment score.

What is Scoring Labels?

Scoring labels are customizable performance categories that classify candidate scores into meaningful performance levels. You define percentage ranges such as 0-30% = Poor and 31-50% = Below Average, then use those labels to categorize and filter candidates by overall assessment score.

How to Set Up Scoring Labels

Open the job you want to update

When creating a new job or editing a job, open the job settings.

Select the Customisation tab

Select the Customisation tab.

Find the AI Evaluation section

On the left side, find the AI Evaluation section.

Open the AI Evaluation tab

Open the AI Evaluation tab.

Open the Scoring Labels tab

Open the Scoring Labels tab to define your performance labels.

Scoring Labels Configuration

  • Poor0-30%. Use this range for candidates whose overall assessment score falls well below the expected threshold.
  • Below Average31-50%. Use this range for candidates who meet only part of the expected criteria.
  • Average51-70%. Use this range for candidates who show acceptable performance with room for improvement.
  • Good71-85%. Use this range for candidates who meet most expectations across the assessment.
  • Excellent86-100%. Use this range for candidates who perform at the highest level.

Best Practices

  • Keep label names short and consistent so they are easy to scan in the UI.
  • Use non-overlapping percentage ranges so each candidate score maps to one label.
  • Align the label ranges with your evaluation rubric before you score candidates.
  • Review labels periodically if your assessment standards change.
  • Use the same scoring scale across similar jobs to support consistent comparisons.

Scoring labels provide a standardized framework for evaluating and categorizing candidates objectively and consistently.