How does this skill help prioritize product features?

It segments feedback by disappointment level, allowing you to prioritize improvements requested by your 'Very Disappointed' users—your core segment—over those who find the product non-essential.

What is the 40% disappointment threshold?

It is an empirical benchmark indicating that if 40% or more of your qualified users would be 'very disappointed' if your product disappeared, you have achieved enough product-market fit to focus on scaling growth.

Who should be surveyed for the Sean Ellis test?

To avoid biased data, only survey users who have experienced the core value proposition, used the product at least twice, and have been active within the last two weeks.

Can I use this for B2B products?

Yes, the framework is highly effective for B2B; simply ensure you are surveying the primary users or decision-makers who interact with the core features rather than tangential stakeholders.

Product-Market Fit Engine (Sean Ellis)

Name: Product-Market Fit Engine (Sean Ellis)
Author: lev-os

bylev-os

0•

マーケティングオートメーション

Measures and optimizes product-market fit using the Sean Ellis 40% disappointment threshold and structured feedback loops.

The Product-Market Fit Engine provides a systematic framework for developers and product leaders to quantitatively measure their product's necessity within a target market. Based on the methodology popularized by growth advisor Sean Ellis, this skill guides users through the core survey process: asking 'How would you feel if you could no longer use this product?' and calculating the 40% disappointment threshold. It helps identify the high-value 'Very Disappointed' segment, extract core benefits for marketing positioning, and prioritize product improvements that directly impact retention and growth readiness.

主な機能

01Standardized 40% disappointment threshold scoring logic

02Longitudinal tracking for measuring PMF impact over time

03Qualified audience segmentation and selection criteria

04Systematic improvement prioritization based on user disappointment levels

05Qualitative feedback extraction for positioning and roadmap planning

060 GitHub stars

ユースケース

01Identifying the specific user personas that derive the most essential value from a product

02Diagnosing weak growth retention and refining product positioning for core users

03Validating product-market fit before scaling acquisition marketing spend

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lev-os/agents pmf-engine-sean-ellis

For use in Claude.ai and ChatGPT

Download Skill