Product-Market Fit (PMF)vsChurn Rate

Product-Market Fit is the degree to which your product satisfies a strong market demand. When you have PMF, customers are actively pulling your product from you rather than you pushing it onto them. Marc Andreessen defined it as 'being in a good market with a product that can satisfy that market.' The Sean Ellis test quantifies it: if 40%+ of users say they'd be 'very disappointed' without your product, you have PMF. Before PMF, nothing else matters — marketing spend is wasted, hiring is premature, and features are guesses. After PMF, everything gets easier: organic growth appears, retention improves, and word-of-mouth starts compounding.

Churn rate measures the percentage of customers who cancel or stop paying during a given time period. It is the silent killer of SaaS businesses — even a small monthly churn compounds into massive annual losses. A 5% monthly churn sounds manageable, but compounded over 12 months, you lose 46% of your customer base. To maintain the same revenue, you need to acquire enough new customers to replace nearly HALF your base every year. This is why the best SaaS companies obsess over churn — Slack's monthly churn below 1% means they retain 89% of customers annually, creating a compounding revenue machine.

Founders declare PMF too early based on vanity metrics — sign-ups, press coverage, 'exciting conversations' with potential customers. True PMF means users would be genuinely disappointed if your product disappeared. The second trap: assuming PMF is binary and permanent. PMF exists on a spectrum and can erode as markets shift (Blackberry had PMF until iPhone changed the market). Also: PMF for one segment doesn't mean PMF for another — you might have PMF with startups but not enterprises.

The trap is tracking only 'logo churn' (customers lost) and ignoring 'revenue churn' (revenue lost from downgrades). You could have 3% logo churn but 8% revenue churn if your largest customers are downgrading. Revenue churn is more dangerous because it hits your top line harder. The second trap: calculating churn from the wrong denominator. Always use start-of-period customers, not end-of-period or average. Using end-of-period inflates your denominator and makes churn look artificially low.

Run the Sean Ellis survey: ask existing users 'How would you feel if you could no longer use [product]?' with options: Very Disappointed, Somewhat Disappointed, Not Disappointed. If 40%+ say 'Very Disappointed,' you likely have PMF. If not, interview the disappointed users to learn what they love, and double down on that specific value. Track the PMF score quarterly — it should improve as you refine the product.

Calculate two churn metrics monthly: Logo Churn = Customers Lost ÷ Start-of-Month Customers × 100. Revenue Churn = MRR Lost (cancellations + downgrades) ÷ Start-of-Month MRR × 100. Implement an exit survey on your cancellation page to identify the #1 reason people leave — the top reason is usually fixable. Target: under 5% monthly for SMB SaaS, under 2% for mid-market, under 1% for enterprise.