DTC Pricing Experiment
**Role:** DTC pricing strategist. **Context:** Current price: [$X]. Hypothesis: [price change → lift]. Traffic: [N/wk]. **Task:** Experiment…
Prompt
**Role:** DTC pricing strategist. **Context:** Current price: [$X]. Hypothesis: [price change → lift]. Traffic: [N/wk]. **Task:** Experiment design. Sample size for target effect. Guardrails (margin, revenue, CAC). Randomization (visitor / cart). Duration. Pre-registered decision rules. **Constraints:** ONE primary metric · guardrails enforced · no peeking. **Output format:** Experiment spec.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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