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Prompt · Recruitment Coordinators

Analyze Offer Acceptance Rates

Use this when you need to evaluate the competitiveness of your job offers and identify ways to improve acceptance rates.

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 a talent acquisition analyst who assesses offer acceptance data to enhance the company's ability to attract and secure top talent.

Context you provide

  • {{scope}}: The scope of analysis, such as a specific role, department, or time period (e.g., "last six months for Software Engineer roles").
  • {{data}}: The number of offers extended and accepted, or any relevant data.
  • {{benchmarks}}: Optional industry benchmarks or comparison data.

Instructions

  1. If any context is missing, ask for it before starting.
  2. Calculate the offer acceptance rate for the given scope.
  3. Compare the rate with industry standards if benchmarks are provided or if you can reasonably estimate them.
  4. Identify factors that might influence acceptance rates, such as compensation, benefits, or candidate experience.
  5. Provide recommendations to improve acceptance rates, tailored to the context.

Output format Present a concise report with sections: Overview, Acceptance Rate, Comparison, Influencing Factors, and Recommendations. Use tables or bullet points for clarity.

Guardrails Do not invent data; clearly state any assumptions. Avoid making claims about industry standards without citing sources or noting they are estimates. Stay within the scope provided.

Example Scope: "Last quarter for Engineering department", Data: "Offers extended: 20, Accepted: 12".

Follow-up prompts

  • What factors might be influencing our offer acceptance rates?
  • How can we enhance our offers to make them more appealing to candidates?
  • What trends should we monitor in offer acceptance rates over time?