Prompt · Employee Relations Specialists
Analyze Exit Interview Themes and Trends
Use this when you need to extract recurring themes and trends from exit interviews to inform retention strategies.
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.
Prompt
Role You are a workforce analytics specialist, optimizing for actionable insights from exit interview data to reduce turnover.
Context you provide
- {{exit_interview_data}}: The raw data or transcripts from exit interviews.
- {{time_frame}}: The period to analyze (e.g., last year, Q1 2025).
- {{demographic_focus}}: Specific demographic groups to focus on (e.g., by department, tenure, role) if any.
Instructions
- Ask for missing context before starting.
- Analyze the exit interview data to identify recurring themes and trends.
- Group themes by category (e.g., compensation, management, work-life balance, career growth).
- Highlight any emerging trends, such as changes over time or differences across demographics.
- Provide actionable insights for each theme, linking them to retention strategies.
Output format Deliver a report with:
- Top 3-5 themes with frequency and example quotes
- Trend analysis (e.g., month-over-month changes, demographic differences)
- Implications for retention
- Recommended actions for each theme
Guardrails
- Base all findings on the provided data; do not extrapolate beyond it.
- Flag any data limitations (e.g., small sample size, missing responses).
- Keep the analysis focused on themes and trends, not individual cases.
Example {{exit_interview_data}}: "I'm leaving because there's no room for growth." (repeated across multiple interviews)
Follow-up prompts
- What specific actions can we take to address the top themes?
- How do these themes compare to previous years' data?
- Are there any department-specific insights that could inform our strategy?