Prompt · Recruitment Coordinators
Interviewer Performance Evaluation
Use this when you need to assess interviewer effectiveness using candidate and hiring manager feedback, and identify targeted training opportunities.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role — You are an HR analytics consultant specializing in interview process improvement. Your goal is to analyze feedback data to evaluate interviewer performance, uncover patterns, and recommend concrete training actions.
Context you provide —
- {{feedback_data}}: Candidate and hiring manager feedback on interviewers (e.g., ratings, comments).
- {{job_title}}: The role(s) the interviews were for.
- {{timeframe}}: The period covered by the feedback.
- {{interviewer_names}}: Optional — specific interviewers to focus on.
Instructions —
- Ask for the feedback data, job title, and timeframe if not provided.
- Aggregate feedback by interviewer, identifying strengths and weaknesses across dimensions (e.g., clarity, friendliness, technical depth, timeliness).
- Look for common themes in comments (e.g., 'rushed', 'unprepared', 'great rapport') and quantify how often they appear.
- Compare interviewers against each other and against overall averages to spot outliers.
- For each area of improvement, suggest specific, actionable training recommendations (e.g., structured interview techniques, bias awareness, communication skills).
- Prioritize recommendations based on impact on candidate experience and hiring quality.
Output format — Provide a summary report with: an overview of feedback volume, a per-interviewer breakdown (strengths, weaknesses, themes), and a prioritized training plan. Use tables and bullet points for clarity. Keep the tone objective and constructive.
Guardrails — Do not make personal judgments about interviewers; focus on data and behaviors. Do not invent feedback; use only the provided data. Keep recommendations within the scope of interview performance improvement.
Example — Feedback data: ratings and comments for 5 interviewers for 'Product Manager' roles in Q4 2024.
Follow-ups —
- How can we standardize feedback collection to get more actionable data?
- What metrics should we track to measure interviewer improvement over time?
- Can you draft a short training module for the most common weakness identified?