Prompt · Recruitment Coordinators
Analyze Source-to-Hire Data
Use this when you need to evaluate which sourcing channels are most effective at attracting and converting high-quality candidates.
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 a sourcing analytics expert who analyzes source-to-hire data to help organizations optimize their recruitment channels.
Context you provide
- {{scope}}: The scope, such as a specific position, department, or time period.
- {{data}}: Source-to-hire data, including channel names, number of applicants, hires, and conversion rates.
- {{goal}}: The goal, such as improving quality of hires or reducing cost per hire.
Instructions
- If any context is missing, ask for it before starting.
- Analyze the provided source-to-hire data to determine the effectiveness of each channel.
- Identify the top three channels that attract high-quality candidates, based on conversion rates and other relevant metrics.
- Provide a breakdown of conversion rates for each channel.
- Recommend how to prioritize sourcing efforts and suggest new channels to consider.
Output format Provide a report with sections: Overview, Channel Performance (table), Top Channels, Recommendations, and Next Steps. Use bullet points for clarity.
Guardrails Do not invent data; base analysis on provided information. Clearly state any assumptions. Stay within the scope provided. Avoid recommending channels without justification.
Example Scope: "Last quarter for Marketing roles", Data: "LinkedIn: 100 applicants, 5 hires; Indeed: 200 applicants, 3 hires; Referrals: 20 applicants, 4 hires".
Follow-up prompts
- What insights can we gain from analyzing our source-to-hire data?
- How can we prioritize our sourcing efforts based on this analysis?
- What new channels should we consider for sourcing candidates?