Product-Market Fit

The Product-Market Fit (PMF) workflow helps you measure whether your product truly satisfies market demand. Using the Sean Ellis survey, retention analysis, and qualitative signals, this guide provides a systematic approach to understanding and achieving PMF.

Overview#

Outcomes#

A successful PMF measurement process delivers:

• Clear PMF score using the Sean Ellis methodology
• Retention benchmarks for your category
• Qualitative understanding of user value
• Action plan to improve PMF if needed
• Confidence to scale (or not)

What is Product-Market Fit?#

Marc Andreessen's definition:

"Product-market fit means being in a good market with a product that can satisfy that market."

In practice, PMF feels like:

• Users actively seeking out your product
• Word-of-mouth growth happening naturally
• Retention curves that flatten (not decline to zero)
• Clear value proposition that resonates

Method 1: Sean Ellis Survey (PMF Score)#

The Question#

Ask users who have experienced your core value:

"How would you feel if you could no longer use [Product]?"

Answer options:

1. Very disappointed
2. Somewhat disappointed
3. Not disappointed

The Benchmark#

40% or more answering "very disappointed" indicates PMF.

Implementation#

Database Schema:

Survey Component:

API Endpoint:

Calculating PMF Score:

When to Send the Survey#

Trigger after users experience core value:

• Completed onboarding
• Used key feature X times
• Been active for Y days
• Reached a milestone

Sample size:

• Minimum: 40 responses for statistical significance
• Ideal: 100+ responses
• Segment by user type for deeper insights

Method 2: Retention Analysis#

Retention Curves#

Retention is the clearest signal of PMF.

Retention SQL Queries#

Daily Retention Cohort:

Retention Benchmarks by Category#

Improving Retention#

Analyze drop-off points:

Identify power users:

Method 3: Qualitative Signals#

Leading Indicators of PMF#

User Interview Questions#

For power users:

1. What would you use if we didn't exist?
2. What problem does [Product] solve for you?
3. Tell me about the last time you used [Product]
4. Who else should be using this?

For churned users:

1. Why did you stop using [Product]?
2. What would have kept you?
3. What are you using instead?

Analyzing Qualitative Data#

Create a signal tracker:

PMF Dashboard#

Key Metrics to Track#

Segmented Analysis#

PMF often exists in specific segments first:

Recommended Agents#

Action Plan Based on Score#

PMF Score < 25%: Major Pivot Needed#

Actions:

1. Talk to 20+ users immediately
2. Identify who (if anyone) is getting value
3. Consider pivoting or major product changes
4. Don't scale - you'll accelerate failure

PMF Score 25-40%: Getting Close#

Actions:

1. Double down on what's working
2. Identify friction points
3. Improve onboarding to core value
4. Test changes with specific segments

PMF Score 40%+: Ready to Scale#

Actions:

1. Document what makes you successful
2. Build repeatable acquisition channels
3. Start scaling team and marketing
4. Continue monitoring PMF as you grow

Deliverables#

Best Practices#

1. Survey regularly - PMF can change over time
2. Segment your data - PMF in one segment first
3. Combine methods - Survey + retention + qualitative
4. Don't fake it - Honest assessment is crucial
5. Act on feedback - Use "somewhat disappointed" insights
6. Be patient - PMF takes time to achieve

Common Pitfalls#

• Surveying too early - Wait for users to experience value
• Small sample size - Need 40+ responses minimum
• Ignoring segments - Overall score masks segment differences
• Premature scaling - Scaling without PMF accelerates failure
• Vanity metrics - Downloads and signups don't equal PMF

Related Workflows#

• Post-Launch - Iterate after launch
• Retention - Improve retention
• Metrics - Track KPIs
• Acquisition - Scale after PMF