CLAUDEBusiness & StrategyINTERMEDIATE Level

Product-Market Fit (PMF) Sean Ellis Survey Analyzer

Battle-tested production AI prompt for product-market fit (pmf) sean ellis survey analyzer. Optimized for CLAUDE with complete parameter placeholders, pro tips, and edge-case handling.

Master Prompt Template•86 words (675 chars)

Open in CLAUDE

Act as a world-class authority and specialist in business. Your task is to execute: **Product-Market Fit (PMF) Sean Ellis Survey Analyzer**. Context & Requirements: - **SURVEY_RESPONSES_CSV:** [INSERT SURVEY_RESPONSES_CSV HERE] - **USER_COHORTS:** [INSERT USER_COHORTS HERE] Execution Rules: 1. **Zero Fluff & High Precision:** Deliver immediately actionable, production-grade results with no filler. 2. **Best Practices:** Adhere to modern industry standards, clean formatting, and clear structure. 3. **Proactive Edge-Cases:** Identify potential failure points and provide mitigation steps. Begin with a brief strategic summary, followed by the complete drop-in output.

Detected Variables & Custom Placeholders:

[INSERT SURVEY_RESPONSES_CSV HERE][INSERT USER_COHORTS HERE]

Replace each bracketed placeholder with your project specifics before submitting to the model.

640 copies•Production-Ready Template

How to Use This Prompt

Copy the prompt, fill in the [SURVEY_RESPONSES_CSV], [USER_COHORTS] placeholders with your project details, and submit to CLAUDE.

Pro Customization Tips:

Be as specific as possible in your variable inputs.
Ask the AI model to explain any non-obvious design decisions.

Practical Limitations & Quality Guardrails

•Fact Verification: Large language models can occasionally produce confident inaccuracies. Always verify specific facts, API library versions, and citations against authoritative documentation.
•Security & Privacy: Never submit production API keys, customer PII, or confidential passwords inside prompt variables.
•Iterative Refinement: If the model omits a constraint, follow up with targeted adjustments (e.g. "Refactor step 2 to adhere strictly to our schema") rather than restarting the chat.

Recommended Setup

Recommended Models:

Claude 3.5 Sonnet or Claude 3.7 Sonnet with Artifacts

Suggested Temperature:

0.4 – 0.6 (Balanced reasoning and clarity)

Target Use Case:

Calculating percentage of users who would be 'very disappointed'.

Model availability and features evolve rapidly. Refer to the provider's documentation for current versions.

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