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Response Relevancy Score

The Response Relevancy Score helps you quickly evaluate how well a candidate’s video response matches the intent of your question.

Alex Harper avatar
Written by Alex Harper
Updated over 3 weeks ago

What is Response Relevancy?

Response Relevancy measures the alignment between what was asked and what the candidate said, assigning a score from 0–100.

This helps you:

  • Screen faster — especially with a large applicant pool

  • Maintain objectivity — consistent, AI-assisted scoring

  • Focus on substance — identify candidates who are thoughtful, relevant, and well-prepared


How the Score is Calculated

Interviewer.AI offers two scoring modes to give you flexibility depending on the type of question:

Flow Type

Reference Used

How It Works

General Flow

No reference provided

The AI evaluates based on knowledge patterns, general context, and language understanding.

Ideal Flow

Your model/ideal answer provided

The AI compares candidate responses against the answer you define for maximum precision.


How to Interpret Scores

Score Range

Meaning

85 – 100

Excellent: Highly relevant, thorough, and well-structured response

70 – 84

Good: Mostly relevant, with only minor gaps

50 – 69

Average: Some alignment, but limited depth or incomplete responses

Below 50

Low: Weak alignment; response does not address the question adequately

Reminder: Relevancy is just one dimension. Use it alongside other metrics like communication skills, confidence, grammar, and personality analysis for a complete evaluation.


Best Practices for Great Results

  1. Choose the Right Flow

    • Use General Flow for broad, situational, or behavioral questions.

    • Use Ideal Flow for technical or role-critical questions (where you already know what a strong response should look like).

  2. Ask Clear, Specific Questions
    Ambiguity lowers scoring accuracy.

    • Poor: “Tell me about a time you worked in a team.”

    • Better: “Describe a situation where you resolved a conflict within a team. What was the outcome?”

  3. Provide Ideal Answers (Where Needed)
    For role-critical or technical questions, supply a strong benchmark answer. This improves accuracy as the AI knows what “good” looks like.

  4. Avoid Overly Open-Ended Questions
    Questions like “Tell me about yourself” do not work well with relevancy scoring. You can disable scoring per question if desired.

  5. Use Skill-Based Categories
    Instead of repeating the same question, group questions under skills.

    Example:

    • Create a skill category such as Problem-Solving

    • Add 10–15 structured situational/behavioral questions

    • The AI will automatically evaluate all responses under that skill

This approach ensures:

  • Candidate responses remain spontaneous

  • Lower probability of coaching/sharing

  • Fair, transparent skill evaluation


Access & Configuration

  • You can enable Response Relevancy at the interview setup stage. Look for the toggle: “Measure Response Relevancy Score.”

  • You can also turn it off for individual questions where relevance scoring is not applicable.


Troubleshooting

  • Relevancy Toggle Missing? Contact support to confirm if your organization has the feature enabled.

  • No Scores Generated? This may occur if:

    • The candidate skipped the question

    • The feature was disabled for that question


Need Help?

For guidance on setting up or optimizing Response Relevancy, contact your Customer Success Manager or reach us at [email protected].


Key Takeaway:
The Response Relevancy Score helps you evaluate responses with speed, consistency, and objectivity, enabling more effective and fair candidate screening.


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