Product-market fit survey (Sean Ellis test)

Test whether a question's wording changes the answers. Respondents are split at random: half are asked about spending on "welfare", half about "assistance to the poor", the General Social Survey pair (Smith 1987; Rasinski 1989). An A/B Condition assigns each person one version, so you can compare the two arms in Results. Swap in your own pair of wordings.

Measures product-market fit among active users using the Sean Ellis 'very disappointed' framework, supplemented by usage patterns, competitive alternatives, and qualitative feedback to identify fit signals and improvement priorities.

Measures product essentiality using the Sean Ellis PMF framework alongside competitive switching risk and perceived differentiation to guide product strategy and roadmap prioritization.

Captures how satisfied customers are with a product, which attributes matter most, and where the experience falls short — for teams tracking product quality, value, and repurchase intent. An AI follow-up interview digs into the real story behind each score instead of a generic star rating.

Captures how a software tool actually performed during a trial, pilot, or proof-of-concept — usability, integrations, support, and value for cost — and ranks which factors matter most to the decision. An AI follow-up interview reconstructs the real story behind the adoption call, including near-misses and blockers. Built for engineering, IT, and product teams running a formal tool evaluation.

Evaluates how easy, efficient, and satisfying your product or website is to use, combining attribute ratings and a prioritization exercise with an AI follow-up that reconstructs a real recent moment of friction instead of relying on vague complaints. Built for product, design, and research teams running ongoing usability tracking.