What is a candidate fit score?
Quick answer
A candidate fit score, or match score, is a number a recruiting tool gives each person to show how closely their profile matches the job's criteria. It is used to rank people, but the number alone hides why: the useful part is the list of criteria met, missed and guessed behind it.
Last updated
Take the free module →Module 17 of the free AI for Recruiting & HR course, about 7 minutes. No account needed.
Updated · By Robert Breen
Why it matters for a small business
Scores make a long list sortable in seconds, which is why almost every AI sourcing and applicant tracking tool shows one. They are a good way to decide who to read first.
They are a poor way to decide who to hire. The top of a ranked list often shares the same score, and one number cannot show that one gap is easy to teach while another is a dealbreaker.
Reading the reasons also protects against AI bias and plain errors: when you can see the evidence, you can spot a criterion that was inferred, misread or simply wrong for the role.
In a real lesson: Pin: Turn 20 AI-Sourced Candidates into a 3-Person Shortlist for Recruiting & HR
In the Pin candidate shortlist lesson the first card shows Fit score 10. Under it, the qualifying question is answered first, then 6 out of 7 Criteria Met, each with its evidence, and an orange dash for the gap: QuickBooks Online.
Most of the top 20 can show the same score, so the lesson has you compare cards on their reasons. One candidate's answers start with "Probably", which means Pin inferred them. Another has 1.4 years total, under the 2 to 4 year range, and is declined as Lacking Experience so the next batch improves.
Try this lesson free or read the step-by-step guide.
Common confusions
Fit score vs lead score
Lead scoring rates how likely a prospect is to buy. A fit score rates how well a person matches a job's requirements.
Fit score vs interview scorecard
An interview scorecard is filled in by people after talking to the candidate. A fit score is computed from a profile before anyone talks.
Stated vs inferred
A criterion marked met because the profile says so is evidence. One marked "probably" is the tool's guess and should become a question.
Tips
- Use the score to choose the reading order, then decide on the evidence.
- For each gap, ask whether it could be taught in the first month.
- Give a reason when you decline; many tools use it to adjust the next batch.
- Never send the score to a candidate as feedback; it is an internal ranking.
Related terms
More Business terms
Where you use it: free lessons
- Pin: Turn 20 AI-Sourced Candidates into a 3-Person Shortlist for Recruiting & HR (Pin, 7 min)
- How AI Answers from Your Documents: Retrieval (RAG) Explained (Stepthrough, 7 min)
- Lusha: Build a Target Account List and Find the Decision Makers for Sales (Lusha, 8 min)
AI tools that use it
Frequently asked questions
- How is a candidate fit score calculated?
- Each tool has its own method, but most compare the profile with the job's criteria (titles, years, skills, location and qualifying answers) and weight the matches. Read the tool's own explanation rather than assuming.
- Is a high fit score enough to shortlist someone?
- No. Check that the criteria behind it are stated on the profile, not inferred, and that any gap is one you can live with.
- Why do so many candidates have the same score?
- Scores often use a short scale, and strong matches cluster at the top. That is why the reasons on each card matter more than the number.