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Business Fundamentals
The Metrics That Actually Matter Pre-Product/Market Fit
Stop tracking vanity metrics. Here are the numbers that actually tell you if you're making progress.
It’s tempting to track everything: page views, downloads, social followers, feature usage. But most metrics are noise. Before product-market fit, only a handful of metrics actually tell you if you’re making progress.
Here’s what to focus on.
The Problem with Vanity Metrics
Vanity metrics make you feel good but don’t inform decisions:
Website traffic: You could have 100,000 visitors and zero customers.
Signups: People sign up out of curiosity. Do they actually use it?
Downloads: Downloads aren’t usage.
Social followers: Followers don’t pay bills.
Total users: If they signed up once and never returned, they’re not users.
The question isn’t “is this number growing?” It’s “does this number predict business success?”
Pre-PMF Metrics That Matter
1. Activation Rate
What it measures: Percentage of signups who experience the core value of your product.
Why it matters: Signups mean nothing if people don’t reach the “aha moment.” Low activation means your onboarding is broken or your product isn’t compelling.
How to measure:
1.
Define your activation event (first project created, first message sent, first report run)
2.
Track: (Users who activate / Total signups) × 100
Benchmarks:
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40%+ is good for most products
•
Below 20% is a red flag
What to do:
•
Simplify onboarding
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Guide users to the core action faster
•
Remove friction before the activation point
2. Retention
What it measures: Do users come back?
Why it matters: Retention is the ultimate test of whether you’re providing value. Growth without retention is a leaky bucket.
How to measure:
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Day 1 retention: % of users who return after 1 day
•
Day 7 retention: % who return after 1 week
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Day 30 retention: % who return after 1 month
Track cohorts—group users by signup date and follow their behavior over time.
Benchmarks:
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Consumer apps: 25% Day 1, 10% Day 30
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SaaS: 40%+ Day 1, 20%+ Day 30
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Great retention curves flatten (stop declining)
What to do:
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Focus on retention before acquisition
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Understand why people churn
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Build habits and recurring value
3. Revenue (or Willingness to Pay)
What it measures: Are people paying you money?
Why it matters: Revenue is the ultimate validation. It proves value better than any survey or engagement metric.
How to measure:
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MRR (Monthly Recurring Revenue)
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Revenue per user (ARPU)
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Conversion rate from free to paid (if freemium)
Pre-revenue alternative: Track willingness to pay through:
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Pre-sales or deposits
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Expressed price sensitivity in conversations
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Upgrade attempts (clicking on paid features)
What to do:
•
Try charging earlier than feels comfortable
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Pay attention to who pays and why
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Don’t over-index on revenue before PMF—usage matters more
4. NPS (Net Promoter Score)
What it measures: Would users recommend you to others?
Why it matters: High NPS correlates with organic growth. It’s a leading indicator of word-of-mouth.
How to measure:
•
Ask: “How likely are you to recommend [product] to a friend or colleague?” (0-10)
•
NPS = % Promoters (9-10) − % Detractors (0-6)
Benchmarks:
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0-20: Decent
•
20-50: Good
•
50+: Excellent
What to do:
•
Follow up with promoters (testimonials, referrals)
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Follow up with detractors (understand why)
•
Track by cohort and segment
5. The Sean Ellis Question
What it measures: Would users be very disappointed without your product?
Why it matters: This is the canonical PMF test. If 40%+ say “very disappointed,” you likely have PMF.
How to measure:
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Survey active users: “How would you feel if you could no longer use [product]?”
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Options: Very disappointed, Somewhat disappointed, Not disappointed
•
Calculate: % who say “Very disappointed”
Benchmarks:
•
40%+ = Strong PMF signal
•
25-40% = Getting there
•
Below 25% = Not yet
What to do:
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Segment responses—who are the “very disappointed” users?
•
Double down on serving them
•
Understand what they value most
Metrics to Ignore (For Now)
Website Traffic
Doesn’t matter until you have conversion working.
Email List Size
Vanity unless they convert.
Social Engagement
Likes and shares don’t pay bills.
Feature Usage Breadth
Users touching many features doesn’t mean they’re getting value.
Competitive Benchmarks
Comparing yourself to others is distracting.
How to Track These Metrics
Keep It Simple
You don’t need enterprise analytics. Simple tools work:
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Amplitude/Mixpanel: Event tracking and cohort analysis
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PostHog: Open source alternative
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Simple dashboards: Google Sheets if needed
Define Events Clearly
Be specific about what you’re measuring:
❌ “User engaged with product”
✅ “User created first project within 24 hours of signup”
Track Cohorts
Aggregate numbers lie. Track users by signup date and follow their behavior over time. This reveals trends averages hide.
Review Weekly
Set a regular cadence:
•
Weekly: Review retention and activation
•
Monthly: Review NPS and revenue trends
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Quarterly: Step back and assess progress
The Dangerous Middle
The most dangerous place is when metrics are “okay”:
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15% retention (not terrible, not great)
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30% Sean Ellis score (close to 40%, but not there)
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Some revenue (but not growing much)
This middle zone can trap you for years. You’re not failing obviously enough to pivot, but not succeeding enough to scale.
If you’re in the middle, push harder on the edges:
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Talk to your most active users—what would make them love it more?
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Talk to churned users—why did they leave?
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Make bigger changes, not incremental tweaks
Metrics After PMF
Once you have PMF, expand your metrics:
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CAC (Customer Acquisition Cost)
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LTV (Lifetime Value)
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Payback period
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Net Revenue Retention
•
Burn multiple
But pre-PMF, these are premature optimizations. Focus on the basics.
Key Takeaways
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Most metrics are vanity—focus on the few that predict success
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Pre-PMF metrics: activation rate, retention, revenue/willingness to pay, NPS, Sean Ellis question
•
40%+ “very disappointed” in the Sean Ellis question signals PMF
•
Track cohorts, not just aggregates
•
The “okay” middle zone is dangerous—push for clear signals
•
Keep tracking simple; sophistication comes later
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