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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.

Written by Alex Harper

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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