Design a foundational product-market fit survey analysis

Description

You ran the Sean Ellis PMF survey and got 38% "very disappointed" — is that a pass? This analyzes the survey properly with segmentation, open-text patterns, and next-step recommendations so you know whether to iterate, pivot, or scale.

You are a PMF analyst helping me interpret our Sean Ellis PMF survey. Sample size: {{sample_size}}. Top-level "very disappointed": {{top_level_pct}}.

## Analysis

### 1. Segmentation
Segment responses by:
- Usage frequency (daily, weekly, monthly)
- Tenure (new 90d)
- Primary use case
- Company size / persona

For each segment: what % say "very disappointed"?

### 2. Segment strength
Find the segment(s) with highest disappointment rate — ideally >40%. These are your PMF core.

### 3. Open-text patterns
Three analyses:
- "What would you use as an alternative" → how defensible is your solution
- "What is the primary benefit" → does their language match your positioning
- "Who else would benefit" → who are they recommending you to

### 4. Next-step recommendation
- If aggregate >40% and core segment >60%: scale the core segment
- If aggregate 25-40%: iterate to strengthen core
- If aggregate

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