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AI scoring weights

Tune how Nextal scores candidate-to-job fit. Adjust the relative weight of skills, experience, salary fit, language levels and location — match the way your organisation evaluates candidates.

Where to find it
Settings → Customization → AI scoring weights
Who can use it
Organisation admins
Direct URL
https://app.nextal.com/conf/aiScoringWeights

The AI scoring weights page controls how Nextal computes the candidate-to-job match score. By default, skills carry the most weight; experience comes second. If your organisation values different signals — say location matters more than skills for retail roles — adjust the weights here.

The scoring weights page. Each dimension has its own slider; the total adds up to 100%.

Opening the page

  1. Open Settings

    Click your avatar or the Settings menu in the top-right.

  2. Go to Customization

    Find the customization section.

  3. Click AI scoring weights

    The dedicated page for tuning the weights opens.

The scoring dimensions

Each dimension has a weight you can adjust. The relative weight determines how much that dimension affects the final match score (out of 100):

Dimension

What it measures

Skills

Overlap between the candidate’s skills and the job’s required skills.

Experience

How well the candidate’s years of experience fit the job’s expected range.

Salary fit

Whether the candidate’s salary expectations fit the job’s salary range.

Language levels

Whether the candidate meets the job’s language requirements.

Location

Distance between the candidate and the job location.

Adjusting the weights

  1. Pick a dimension

    Click or drag its slider.

  2. Move the slider

    Higher weight = the dimension counts more in the final score.

  3. Save

    The changes apply to new score computations immediately. Existing scores don’t recalculate retroactively unless you trigger a re-score.

When to tune the weights

  • Your team consistently rates the AI score wrong. If recruiters keep saying “this 85-match isn’t actually a good fit,” lower the weight on whatever the AI is weighting too high.
  • You add a new vertical. Healthcare hiring values language levels and certifications; tech hiring values skills and experience. Different organisations value different things.
  • You change your job description style. If you start listing 30 skills per job (instead of the 5 essential ones), the skills weight might need to come down to compensate.

Who can do what

What you want to do

What you need

View the page

Organisation admin access

Adjust and save weights

Same

Tips

  • Change one weight at a time. Bumping three weights at once makes it hard to see which change actually helped your match quality.
  • Re-evaluate quarterly. What works in Q1 may not work in Q4 — market conditions, candidate pool, and your own recruiting priorities all shift.
  • Document why you changed. Drop a note in the comments on a few representative jobs explaining the change — useful when a new teammate asks why the scores look different.