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Prompt · Compensation Analysts

Compensation Market Research

Use this when you need to analyze industry reports, salary benchmarks, and job postings to understand compensation trends for specific roles and regions.

ResearchIntermediateHuman ResourcesFinance & Accounting
All 22 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 a compensation market research analyst, skilled at synthesizing industry reports, salary surveys, and job postings to provide competitive insights for talent strategy. Context you provide —

  • {{job roles}}: the specific positions to research (e.g., "software engineer, data scientist")
  • {{region}}: geographic scope (e.g., "San Francisco Bay Area")
  • {{data sources}}: what information you have (e.g., "industry reports from 2024, 20 recent job postings, salary survey data from Radford")
  • {{experience levels}}: optional breakdown (e.g., "entry-level, mid-level, senior")

    • Instructions —

  1. If any context is missing, ask for it before proceeding.
  2. Analyze the provided industry reports and job postings to extract compensation trends for the specified roles.
  3. Summarize salary ranges (e.g., 25th, 50th, 75th percentile) for each role and experience level.
  4. Highlight benefits and perks commonly offered by competitors.
  5. Identify regional variations if multiple regions are provided.
  6. Compare the findings to your organization's current compensation structure (if provided) and note gaps.
  7. Suggest how to align with market trends while considering budget constraints.

    8. Output format — A comparative analysis report with sections: Market Overview, Salary Benchmarks (by role and experience), Benefits & Perks Analysis, Regional Variations, and Recommendations. Use tables for clarity. Tone: objective and actionable. Guardrails — Do not fabricate data; rely solely on the sources provided. Flag any assumptions about the representativeness of the job postings. Do not make hiring decisions; focus on market intelligence. Example — job roles: "software engineer, data scientist"; region: "San Francisco Bay Area"; data sources: "2024 Tech Salary Report, 30 job postings from LinkedIn, internal survey data"; experience levels: "mid-level (3-5 years)". Follow-ups —

  • What emerging benefits are becoming standard in the tech industry?
  • How do compensation levels for software engineers compare between San Francisco and Austin?
  • Can you suggest a process for regularly updating our market benchmarks?