Two signals of product-market fit. The PMF survey asks users a single question. Retention curves watch what they actually do. Each catches what the other misses.
Last updated: 2026-04-01
A single survey question popularized by Sean Ellis: "How would you feel if you could no longer use this product?" A commonly used survey benchmark is 40% or more of users answering "very disappointed". Superhuman's account describes using this survey approach.
Best for early-stage products with active users but limited cohort data. Gives a signal in days, not months.
Cohort retention plotted over time. For each cohort, you track what percentage are still active at D7, D14, D30, D60, D90. One signal is the curve flattening to a plateau over a meaningful period.
Best for products with at least three to six months of cohort data. The observation period should match the expected usage cycle.
Survey score = Very disappointed respondents / Total qualified respondents x 100The 40% guideline is a signal for the surveyed segment, not proof of product-market fit. PM Toolkit uses a broader composite PMF score, which is a different measure.
For each cohort: Active users in the return window / Starting cohort size x 100Define the activity and return window first. A stable plateau can suggest lasting use; its meaning depends on the product and cohort size.
| Criteria | PMF Survey | Retention Curves |
|---|---|---|
| Type of signal | Stated preference | Behavioral data |
| Time to result | Days | Months |
| Threshold | 40%+ "very disappointed" | Curve flattens to a stable plateau |
| Origin | Sean Ellis survey method | Cohort analysis tradition; Andrew Chen popularized for PMF |
| Sample size | Choose sample size for the precision needed | Multiple cohorts of meaningful size |
| Risk of false positive | Higher. Self-selecting respondents | Tracking errors or required usage can mislead |
| Pairs with | NPS, jobs-to-be-done research | LTV, churn, cohort analysis |
| Best stage | Early product launch | Growth and scaling stage |
Pros
Cons
Pros
Cons
Use your own inputs to explore the calculations and compare results.
Sean Ellis's guideline looks for at least 40% of qualified respondents saying they would be very disappointed without the product. Treat it as a signal about that segment. Sampling uncertainty matters, especially near the threshold.
Yes. Respondents may be more engaged than other users, or people may value a product without needing it often. Compare the same segment and usage period, then investigate the gap.
A curve that stabilizes over a meaningful period can indicate continued use by part of a cohort. The plateau height and timing depend on the product, return window, and user segment. There is no universal D30 threshold for product-market fit.
Choose the sample size based on how precise the estimate needs to be. Report respondent counts for each segment, and survey users who have experienced the core product. A fixed 100-response cutoff does not make smaller samples meaningless or larger samples unbiased.
Yes, when you can. The survey measures how much users say they would miss the product; retention measures return behavior. Read both alongside willingness to pay and customer research. Neither alone establishes product-market fit.