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Foundation · Startup

Product-Market Fit Scorecard

Product-Market Fit (PMF) is the most important milestone for any startup — the point where your product satisfies a strong market demand. This scorecard combines Sean Ellis's famous 'very disappointed' survey (would 40%+ of users be very disappointed without your product?) with retention metrics and qualitative signals to give you a holistic PMF assessment. PMF isn't binary — it's a spectrum, and this scorecard helps you measure where you are.

When to use this framework

  • You're pre-PMF and need to track progress toward it
  • You think you have PMF but want to validate with data
  • Investors ask 'Do you have product-market fit?' and you need a rigorous answer
  • You're deciding whether to invest in growth (premature scaling without PMF is the #1 startup killer)
  • You want to compare PMF across different customer segments

Before you start

You need at least 30-40 active users to run the Sean Ellis survey with statistical significance. For retention data, you need at least 2-3 months of cohort data.

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Worked Example

Superhuman (2018)

1. Sean Ellis Survey Results

Ask active users: 'How would you feel if you could no longer use [product]?' The magic threshold is 40% selecting 'Very disappointed.'

How many users responded to the survey? Aim for 30+ for meaningful results.

150

Percentage who answered 'Very disappointed.' The PMF threshold is 40%+.

58

Percentage who answered 'Somewhat disappointed.'

30

Percentage who answered 'Not disappointed.' These users don't see enough value.

12

2. Retention Metrics

Percentage of new users who return in Week 1.

65

Percentage of new users who return in Month 1.

55

Percentage of new users still active after 3 months. If the retention curve flattens, that's a strong PMF signal.

50

Does your retention curve flatten (PMF!) or keep declining toward zero (no PMF)?

flattening

3. Qualitative PMF Signals

Rate each signal from 1 (not at all) to 10 (absolutely yes).

Are users telling others about your product without being asked? Are you seeing organic signups?

7

Are users using the product as often as you'd expect (daily for a daily-use product, weekly for weekly)?

9

Are users willing to pay (or pay more) for the product? Do they complain about price or gladly pay?

8

When the product has downtime or bugs, do users complain loudly? Strong complaints = they depend on you = PMF.

10

4. PMF Assessment

Average of the four qualitative signals.

Based on all signals above, where are you on the PMF spectrum? What's the evidence?

Strong PMF for the core segment (power email users, professionals who process 100+ emails/day). Evidence: 58% 'very disappointed' (well above 40% threshold), flattening retention at 50% M3 (exceptional for a productivity tool), and users are vocally upset during any downtime. Rahul Vohra documented this process in his famous First Round article — he segmented the survey by persona and found PMF was strongest among 'busy professionals who care about speed and design' and weakest among 'casual email users.' This segmentation insight led them to double down on the power user segment rather than trying to broaden the product prematurely.

If pre-PMF: what must you change to get there? If post-PMF: what's your growth strategy?

1. DO: Invest in growth for the core segment (founders, executives, VCs who process 100+ emails/day). 2. DO: Improve the product for 'somewhat disappointed' users — understand what's missing for them and whether it's worth addressing. 3. DON'T: Try to make the product work for 'not disappointed' users — they're not the target. 4. DO: Segment the survey by user type to find which personas have the strongest PMF. 5. DO: Use the 'very disappointed' users as the basis for positioning and testimonials — they're your best advocates.
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