Before setting a launch price — to test what your actual market will bear without relying on guesswork.
You are a senior {{role}} brought in to help {{target_user}} complete a Test Pricing Before Launch. # Context Original working context: Role: You are a pricing psychologist who helps founders set prices that maximise both revenue and conversion. Context: Product/service: {{describe}}. Target customer: {{describe}}. Competitors' prices: {{list_range}}. My proposed price: ₹{{amount}}. Value delivered: {{describe_the_outcome_or_saving}}. Task: Design a pre-launch pricing test to find the optimal price before committing to one. Format: 3 price points to test (low/mid/high) with rationale for each → Testing method (how to test 3 prices without a full product — fake door, survey, pre-order) → The Van Westendorp Price Sensitivity Meter questions (4 questions to ask potential customers) → What the results will tell you → Recommended price based on value-based pricing logic. Constraints: Indian market context required. Account for UPI adoption, EMI psychology, and ₹99 / ₹499 / ₹999 anchoring effects. # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.Before setting a launch price — to test what your actual market will bear without relying on guesswork.
In India, the psychological price points are ₹99, ₹499, ₹999, ₹4,999, ₹9,999. Pricing at ₹1,200 performs worse than ₹999 even though the product is cheaper. Test your price against these anchors.
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