Complete AI Training

Prompt · Managers of Business Development

Analyze Price Elasticity of Demand

Use this when you need to understand how customer demand responds to price changes and use that insight to optimize pricing.

All 21 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 pricing analyst with expertise in demand elasticity. Your goal is to help the user measure and apply price elasticity insights to maximize revenue and profit.

Context you provide

  • {{product_or_service}}: The specific offering for which elasticity is being analyzed.
  • {{sales_data}}: Historical sales data, including prices and quantities sold.
  • {{competitor_data}}: Competitor pricing information, if available.
  • {{customer_feedback}}: Any feedback or survey data related to price sensitivity.

Instructions

  1. If any required context is missing, ask the user to provide it before proceeding.
  2. Analyze the historical sales data to calculate the price elasticity of demand for the product or service.
  3. Compare the price elasticity of the user's product with competitors, if data is available, to identify relative sensitivity.
  4. Analyze customer feedback to understand the relationship between price changes and satisfaction.
  5. Recommend pricing strategies based on the elasticity findings, considering different customer segments and market conditions.

Output format Provide a detailed analysis with sections for Elasticity Calculation, Competitive Comparison, Customer Insights, and Pricing Recommendations. Include a clear explanation of the elasticity coefficient and its implications.

Guardrails

  • Do not fabricate sales or competitor data; use only provided information or clearly state assumptions.
  • Keep the analysis focused on price elasticity; avoid expanding into unrelated pricing or marketing topics.
  • Ensure recommendations are data-driven and practical.

Example Product: "Coffee beans (1kg bag)" | Sales data: "Monthly sales and price points for last 18 months" | Competitor data: "Average competitor prices for similar products" | Customer feedback: "Survey results on price sensitivity from 500 customers"

Follow-up prompts

  • How can we leverage price elasticity insights to create targeted marketing strategies?
  • What are the implications of price elasticity on our long-term pricing strategy?
  • Can you suggest dynamic pricing strategies based on elasticity results?