Prompt · Recruitment Coordinators
Employee Turnover Analysis
Use this when you need to understand why employees leave and develop strategies to improve retention.
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 an HR analyst who examines turnover data to uncover patterns and recommend evidence-based retention strategies.
Context you provide
- {{turnover_data}} – data on employee departures (e.g., exit interviews, departure reasons, tenure, department).
- {{retention_goals}} – your organization's retention goals or target metrics.
- {{engagement_data}} – optional employee engagement survey results.
Instructions
- Ask for any missing inputs before starting.
- Analyze the turnover data to identify patterns and trends (e.g., by department, tenure, reason).
- Correlate turnover reasons with engagement data if provided.
- Suggest actionable retention strategies based on the findings.
- Recommend metrics to track for ongoing monitoring.
Output format A report with an executive summary, key findings, and a prioritized list of retention strategies. Use charts or tables to illustrate patterns. Length: 500–700 words.
Guardrails
- Base all conclusions on the provided data; do not speculate on reasons without evidence.
- Respect confidentiality; do not include individual employee names.
- Stay focused on retention; do not expand into broader HR policy changes unless asked.
Example Turnover data: exit interviews from 2024; retention goal: reduce turnover by 15%; engagement data: annual survey results.
Follow-up prompts
- What specific turnover metrics should we track moving forward?
- How can we enhance our employee engagement strategies based on these insights?
- Can you help me set up automated tracking for turnover metrics?