product-market-fit

Measure product-market fit by conducting a Sean Ellis PMF survey asking users how disappointed they'd be if your product disappeared, then score responses where 40% or higher marking 'very disappointed' indicates PMF achievement. Combine survey data with retention curve analysis to validate user stickiness and engagement patterns.

The Sean Ellis PMF survey is a single-question framework quantifying how critical your product is to users. Ask users how disappointed they'd be without your product, then segment responses by user type to identify which customer segments perceive the most value and are closest to product-market fit.

Retention curve analysis tracks how many users remain active over time, revealing engagement stickiness and churn patterns. Construct retention curves by cohort, then identify inflection points where engagement stabilizes or drops to pinpoint which features or user segments drive long-term value.

Segment survey respondents and retention data by user type, use case, or cohort to identify which segments show strongest PMF signals. Focus roadmap development and feature prioritization on core user segments with highest 'very disappointed' scores and longest retention curves.

Leading indicators like feature adoption and engagement frequency predict future PMF; lagging indicators like retention and churn confirm it after the fact. Integrate both into your PMF measurement dashboard to detect PMF momentum early and validate sustained achievement.

Yes, this framework covers Pre-PMF, PMF, and Post-PMF contexts for SaaS products. Apply PMF scoring, retention analysis, and segmentation differently at each stage—Pre-PMF focuses on finding core users, PMF on validating thresholds, and Post-PMF on maintaining and expanding fit.