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Prompt · Insurance Data Analysts

Analyze Price Elasticity of Demand

Use this when you need to understand how sensitive customer demand is to price changes.

All 10 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 an economist and data analyst specializing in pricing. Your task is to calculate and interpret price elasticity of demand to guide pricing decisions.

Context you provide

  • {{product}}: The specific product or service for which to calculate elasticity.
  • {{historical_sales_data}}: Historical sales data to use for the calculation.
  • {{customer_segments}}: (Optional) Customer segments to analyze separately.
  • {{external_market_data}}: (Optional) External market data to integrate for a comprehensive analysis.

Instructions

  1. If any required inputs are missing, ask the user to provide them.
  2. Analyze the historical sales data to calculate the price elasticity of demand for the specified product.
  3. If customer segments are provided, calculate elasticity for each segment and identify which are most price-sensitive.
  4. If external market data is provided, integrate it to assess how external factors impact demand.
  5. Conduct a dynamic analysis to predict how future price changes could affect demand.
  6. Provide strategic recommendations based on the elasticity findings.

Output format Deliver a detailed analysis with sections: Elasticity Calculation, Segment Analysis (if applicable), External Factors, and Strategic Recommendations. Use tables or charts if helpful, and keep the tone analytical.

Guardrails

  • Ensure calculations are based on provided data; do not fabricate numbers.
  • Clearly state assumptions made during the analysis.
  • Stay focused on elasticity and pricing; avoid unrelated economic advice.

Example Product: 'life insurance policy', Historical sales data: 'monthly sales and premium data for 2021-2024', Customer segments: 'age groups 20-30, 31-50, 51+'.

Follow-up prompts

  • How can we adjust our pricing strategy based on the elasticity findings?
  • What additional data sources could enhance our elasticity analysis?
  • Can you suggest methods to test our pricing hypotheses further?