PMF Survey Skill | Agent Skills

PMF Survey

Create and analyze a Product-Market Fit survey using Rahul Vohra's Superhuman framework.

Entry Point

When this skill is invoked, start with:

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 PMF SURVEY
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The magic number: >40% "very disappointed" = PMF

What do you want to do?

  1. Create a PMF survey
     → Generate the four questions + implementation guide

  2. Analyze existing results
     → Paste your data, get PMF score + action plan

  3. Understand the framework
     → Learn when and how to use this

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What This Does

Guides you through running Sean Ellis's PMF survey with Rahul Vohra's systematic approach:

The magic "very disappointed" >40% benchmark
Four-question survey structure
Segment analysis by high-expectation customers
Actionable improvement plan

Usage

/pmf-survey

Optional parameters:

/pmf-survey --create - Generate survey questions
/pmf-survey --analyze [data] - Analyze existing survey results
/pmf-survey --export - Export survey to Typeform/Google Forms format

What Happens

Mode 1: Create Survey

Validates readiness:
- Do you have users who experienced the core product?
- Have they used it at least twice in last 2 weeks?
Generates four-question survey:
- Q1: How disappointed if you could no longer use [product]?
- Q2: What type of people would most benefit?
- Q3: What is the main benefit you receive?
- Q4: What can be improved?
Provides implementation guidance:
- Who to survey (active users, not everyone)
- Survey tool recommendations
- Sample size calculations

Mode 2: Analyze Results

Calculates PMF score:
- % who answered "very disappointed"
- Benchmark: >40% = PMF, <40% = not yet
Segments users:
- Very disappointed (supporters)
- Somewhat disappointed (neutrals)
- Not disappointed (detractors)
Identifies high-expectation customers:
- From "what type of people" answers
- Your most discerning potential users
Generates improvement plan:
- What to double down on (from supporters)
- What to ignore (from detractors)
- How to convert neutrals

Example Output (Analysis Mode)

📊 PMF Survey Analysis

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🎯 PMF SCORE: 58%
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✅ STRONG PMF (>40% very disappointed)

Responses: 250 total
- 145 (58%) - Very disappointed 🟢
- 72 (29%) - Somewhat disappointed 🟡
- 33 (13%) - Not disappointed 🔴

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👥 HIGH-EXPECTATION CUSTOMERS
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From "What type of people benefit most?":
1. Technical founders at early-stage startups (mentioned 89 times)
2. Solo developers building side projects (mentioned 67 times)
3. Remote engineering teams (mentioned 54 times)

Focus: Technical founders at early-stage startups
Why: Most discerning, strongest advocates, willing to pay

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💡 MAIN BENEFITS (from supporters)
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Top themes:
1. "Saves me 10+ hours/week on documentation" (92 mentions)
2. "Makes code review actually enjoyable" (78 mentions)
3. "Onboards new devs 3x faster" (65 mentions)

🎯 Your core value prop: Time-saving documentation + code review

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🔧 IMPROVEMENTS NEEDED
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From supporters (PRIORITIZE):
1. "Better GitHub integration" (45 mentions) → Build this
2. "Slack notifications" (38 mentions) → Build this
3. "Team analytics dashboard" (31 mentions) → Build this

From neutrals (CONSIDER):
1. "More customization options" (22 mentions) → Maybe
2. "Mobile app" (18 mentions) → Later

From detractors (IGNORE):
1. "Should be totally free" (12 mentions) → Wrong segment
2. "Too focused on documentation" (8 mentions) → Not our market

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📋 ACTION PLAN
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✅ DOUBLE DOWN (you have PMF, now optimize):

1. Focus on high-expectation customer:
   "Technical founders at early-stage startups"

2. Amplify core benefits:
   - Time-saving documentation
   - Code review improvements
   - Faster onboarding

3. Build supporter requests:
   Priority 1: Better GitHub integration
   Priority 2: Slack notifications
   Priority 3: Team analytics

4. Ignore detractor feedback:
   - Wrong pricing expectations = wrong segment
   - "Too focused" = they're not your market

🎯 GROWTH STRATEGY

Now that you have PMF (58% > 40%):
- Segment marketing to "technical founders at early-stage startups"
- Lead with "Save 10+ hours/week on documentation"
- Build supporter-requested features
- Survey again in 3 months to measure improvement

Learn More

See the full PMF Survey framework at: frameworks/measurement/pmf-survey.md

Framework: Rahul Vohra (Superhuman) based on Sean Ellis Best for: Measuring PMF, prioritizing improvements, identifying target market Magic number: >40% "very disappointed" = PMF

Agent Skills: PMF Survey

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