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Understanding Scoring in RightMatch AI
Understanding Scoring in RightMatch AI
Sterling Smith avatar
Written by Sterling Smith
Updated over 2 months ago

Welcome to the RightMatch AI Knowledge Base. This article provides a comprehensive overview of how scoring works within our platform, helping you make the most informed hiring decisions.


Interview Scoring

Question Scoring

  • Scoring Range: Each question is scored on a scale from 1 to 5 based on the candidate’s answer.

  • Scoring Criteria: The scoring takes into account:

  • The applicant’s response.

  • The skill level designated in the interview (e.g., Beginner, Intermediate, Expert).

  • The job description.

  • The specific skills associated with the question.

  • Unanswered Questions: If a question is left unanswered, it receives a score of 0.

Skill Scores

  • Aggregation: Question scores are aggregated by skill to form overall skill scores.

  • Multiple Skills per Question:

    • If a question pertains to multiple skills, it is proportionally weighted for each skill.

    • Questions associated with a single skill carry more weight for that particular skill.

Aptitude Score

  • Calculation: The aptitude score is a weighted average of the individual skill scores.

  • Weighting Factors: Skills are weighted based on their designated skill level:

  • Expert skills have a higher weight.

  • Beginner skills have a lower weight.

Custom Scores and Models

  • Team Input: Custom scores provided by your team members are integrated into the model, enriching the context for future interviews.

  • Model Updates: A new custom model is generated after every 25 custom scores are added, ensuring the model stays current with your team’s insights.


Resume Scoring

Skills and Work Experience Extraction

  • Data Extraction: The system extracts relevant skills and work experience from the candidate’s uploaded resume (in PDF or DOCX format).

  • Comparison Basis: These extracted elements are compared against the job description to evaluate fit.

Scoring Weightage

  • Work Experience: Holds the highest weight in the resume scoring algorithm at 70%.

  • Skills: Contribute 30% to the overall resume score.

  • Rationale: This weighting reflects the greater importance of practical experience in most job roles.

Custom Models

  • Continuous Improvement: Similar to interview scoring, a new custom resume scoring model is generated after every 25 custom scores are added.

  • Customization: This allows the model to adapt to specific criteria and preferences unique to your organization.


Important Notes

Video and Transcript Usage

  • Video Content: The candidate’s video is not used in the scoring process.

  • Transcript Reliance: Only the transcript of their answers is considered, ensuring a focus on content over presentation.

Spelling and Grammar Considerations

  • AI-Generated Transcripts: Since transcripts are generated by AI, spelling mistakes from the candidate are not penalized.

  • Text-Based Interviews: For interviews conducted via text, spelling and grammar are evaluated and can impact the score.

Trust Score

  • Independence from Performance: The trust score is independent of the candidate’s interview or resume performance.

  • Determining Factors: It is solely influenced by the candidate’s browser events during the interview process.


Thank you for using RightMatch AI. We hope this guide clarifies how our scoring system works to provide you with the best candidate evaluations. If you have any further questions, please don’t hesitate to contact our support team.

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