Product-market fit survey template

This product-market fit survey opens with a usage screener and then asks the Sean Ellis question: how disappointed someone would be if they could no longer use [Product]. AI-moderated follow-ups examine who benefits most, the product's core value, and what participants would use as an alternative.

What this template measures

The first question is a behavioral screener tied to the product's core action. Define the action and qualification threshold before launch so the product-market fit measure comes from people with enough recent experience to assess the product.

The core measure keeps the canonical options, Very disappointed, Somewhat disappointed, and Not disappointed, in their standard order. Four AI Questions then explore best-fit users, the main benefit, replacement behavior, and possible improvements without assuming the product should be indispensable. A usage-context question provides a relevant way to segment the result.

Who it's for

This template is for product managers and product marketers checking fit after a launch, before a fundraising or planning cycle, or on a recurring cadence. It also suits founders evaluating an early product with a first cohort of engaged users and teams investigating the reasons behind a product-market fit measure.

How the AI moderator probes

The AI Question type examines the reasoning behind the fixed-choice PMF response. If someone answers "very disappointed," the moderator asks what would change in their day-to-day work without the product. If a participant names a workaround, such as a spreadsheet or competitor, the moderator asks how it compares. If the improvement answer is vague, such as "make it faster," it probes for the specific moment when speed matters.

Follow-ups adapt to the participant's wording, so two "very disappointed" respondents can give different underlying reasons. AI follow-up questions: probing without a moderator explains the adaptive probing.

Tips before you launch

Replace the "[Product]" and "[completed core action]" placeholders before sending. Keep the audience narrow to people who have used the product, and use account data for plan, tenure, company size, or use case when available instead of asking participants to recall information you already hold. How to write screener questions that actually screen provides guidance for adding filters.

Run this survey on a recurring cadence, such as quarterly or after a major release, to track changes over time. Group the "who benefits most" and "main benefit" answers, then compare them by usage context and recent core-action frequency. Keep the qualifying threshold and audience definition stable between waves.