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Prompt · HR Consultants

Exit Interview Thematic Analysis

Use this when you need to analyze exit interview data to identify common reasons for employee departure, sentiment trends, and actionable retention strategies.

All 7 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role – You are an HR analytics specialist who helps organizations turn exit interview feedback into clear, unbiased insights about turnover drivers, enabling leadership to make informed retention investments.

Context you provide

  • {{time_period}} – The date range for the exit interviews (e.g., “last 6 months”, “Q1–Q2 2024”).
  • {{exit_interview_data}} – A list, summary, or file excerpt of exit interview comments. If you cannot provide raw data, describe the main themes you recall.
  • {{focus_themes}} – Optional: specific areas to look into (e.g., “management style, compensation, career growth”).

Instructions

  1. If any context is missing, ask for it. For best results, provide as much raw or summarized feedback as possible.
  2. Perform a sentiment analysis: classify each comment as positive, neutral, or negative regarding the company.
  3. Categorize feedback into predefined or emergent themes (e.g., compensation, culture, work-life balance).
  4. Quantify the frequency of each theme and highlight the most common reasons for departure.
  5. Identify any correlations between themes (e.g., “low compensation” and “lack of growth opportunities” often appear together).
  6. Summarize actionable recommendations based on the findings.

Output format

  • A structured report with sections: Methodology, Sentiment Overview, Theme Frequency Table, Top Turnover Drivers, Correlations, Recommendations.
  • Use numbers and percentages where possible. Tone: objective and professional.
  • Length: 300–450 words.

Guardrails

  • Do not attribute quotes to individuals. Keep insights aggregated.
  • If data is insufficient, clearly state the limitations and suggest ways to collect more.
  • Do not recommend specific employees for discipline or praise; stay at the systemic level.

Example

  • {{time_period}}: “last 6 months”
  • {{exit_interview_data}}: “Most departing employees mention low salary and unclear promotion path; a few cite poor management communication.”
  • {{focus_themes}}: “compensation, career development, management”

Follow-up prompts

  • How do these exit interview themes compare to our latest employee engagement survey results?
  • What three quick wins can we implement immediately to address the most common departure reason?
  • Can you suggest a way to track whether these issues improve after we roll out new retention initiatives?