# Pmf Leading Indicator Assessment > Evaluate product-market fit using the Sean Ellis Test. Use this skill when you have a live MVP and need a leading indicator of fit before investing in growth, when retention is low and you need to diagnose the cause, or when you need to identify your "must-have" user segment to refine positioning. - Skill: `samarv/pmf-leading-indicator-assessment` (Agent Skill) - Install (CLI): `npx skillmds@latest add samarv/pmf-leading-indicator-assessment` - Raw SKILL.md: https://api.skillmd.com/api/skills/samarv/pmf-leading-indicator-assessment/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: samarv (https://skillmd.com/u/samarv) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/samarv/pmf-leading-indicator-assessment --- The Sean Ellis Test (or "The 40% Test") provides a leading indicator of product-market fit. While retention cohorts are the ultimate "lagging" proof of fit, this survey allows you to identify if you have a "must-have" product day one, without waiting months for data to mature. ## 1. Segment the Audience Do not survey everyone. Surveying people who have only seen a demo or just signed up will result in "noise." * **Target:** Users who have experienced the "core" of the product. * **Criteria:** Must have used the product at least twice. * **Recency:** Must have used the product within the last 1–2 weeks (active users, not churned users). * **Sample Size:** Aim for at least 30–50 responses for valid initial signal. ## 2. Deploy the Primary Question Ask the single most important question to gauge "must-have" status: **"How would you feel if you could no longer use [Product Name]?"** 1. **Very disappointed** (The "Must-Have" group) 2. **Somewhat disappointed** (The "Nice-to-Have" group) 3. **Not disappointed** 4. **N/A – I no longer use the product** ## 3. Analyze the Threshold * **40% or higher "Very Disappointed":** You have found a "must-have" vein. You are ready to focus on activation and sustainable growth. * **Below 40%:** You are likely in a "commodity" state or targeting the wrong segment. Do not scale marketing yet; you will waste capital. ## 4. Extract the "Must-Have" Benefit For the users who said they would be **Very Disappointed**, run a follow-up qualitative analysis to understand why they care. ### Step A: Open-Ended Discovery Ask: "What is the primary benefit that you get from [Product]?" and "Why is that benefit important to you?" * Look for recurring language or "hooks" (e.g., "I'm drowning in email"). ### Step B: Benefit Validation (Multiple Choice) Once you have 4–5 recurring themes, survey a *different* group of users. * **Question:** "Which of these is the primary benefit you receive?" (Force a choice between the 4–5 themes). * **Question:** "What would you use if this product were no longer available?" (Identifies the true competition). ## 5. Move the Score (The "Lookout" Strategy) If your score is low (e.g., 10-15%), use this workflow to reach the 40% threshold: 1. **Isolate the "Very Disappointed" group:** Even if it's only 7%, find out who they are and what feature they use. 2. **Reposition the Hook:** Update marketing and landing pages to focus *exclusively* on the specific benefit that 7% loved. 3. **Streamline Onboarding:** Remove any steps that don't lead directly to that specific benefit. Ensure "Speed to Value" (Aha Moment) happens in the first session. 4. **Ignore the "Somewhat Disappointed" users:** Do not build features for them yet. Trying to please everyone dilutes the product for your "must-have" core. --- **Example 1: Mobile Security (Lookout)** * **Context:** A mobile app with backup, phone-finding, and antivirus features had only a 7% PMF score. * **Insight:** The 7% who loved it cared exclusively about "Antivirus," even though phone viruses were rare at the time. * **Application:** The team repositioned all marketing on "Antivirus" and changed onboarding so the first thing a user saw was an "Antivirus Scanning" progress bar. * **Output:** The score jumped to 40% in two weeks because the product now attracted people seeking that specific value and delivered it immediately. **Example 2: Productivity Tool (Xobni)** * **Context:** Testing the primary benefit of an email plugin. * **Input:** Users were asked "Why is finding things faster important to you?" * **Application:** Qualitative responses repeatedly used the phrase "I'm drowning in email." * **Output:** The marketing was changed to lead with the "Drowning in email?" hook, which significantly increased the conversion of users who eventually became "Very Disappointed" must-have users. --- ## Common Pitfalls * **Surveying Demos:** Asking "would you use this?" is useless. Only survey users who have actually performed the core action. * **The "Somewhat Disappointed" Trap:** Trying to convert "Somewhat Disappointed" users by adding their requested features. This often results in a mediocre product that is "good for everyone but great for no one." * **Ignoring Context:** Not asking *why* a benefit is important. The "why" provides the emotional context needed for high-performing acquisition copy. * **Premature Scaling:** Stepping on the gas (paid ads) when the score is at 15%. This results in high churn and "leaky bucket" syndrome.