How do I install the Funnel Analysis skill?

Run npx skillmds@latest add nandanosql/funnel-analysis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Funnel Analysis safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Funnel Analysis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Funnel Analysis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Funnel Analysis?

nandanosql (@nandanosql) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Funnel Analysis by nandanosql — Agent Skill

Name: Funnel Analysis
Author: nandanosql

File contents

Purpose

Build and analyze conversion funnels to identify where users drop off, why they leave, and what to fix — turning raw event data into prioritized improvement campaigns.

Application

Step 1: Define the Funnel

## Funnel: [Name — e.g., "Trial to Paid"]

| Step | Event | Definition |
|------|-------|-----------|
| 1 | [Landing page visit] | [User arrives on landing page] |
| 2 | [Signup started] | [User clicks "Start trial"] |
| 3 | [Signup completed] | [User completes registration] |
| 4 | [Onboarding started] | [User begins setup] |
| 5 | [Activated] | [User completes activation event] |
| 6 | [Converted] | [User starts paid subscription] |

Step 2: Measure Conversion

| Step | Users | Conv. Rate | Drop-off |
|------|-------|-----------|---------|
| Landing page | 10,000 | — | — |
| Signup started | 3,200 | 32% | 68% |
| Signup completed | 2,400 | 75% | 25% |
| Onboarding | 1,800 | 75% | 25% |
| Activated | 670 | 37% | 63% |
| Converted | 252 | 38% | 62% |

**Overall funnel conversion:** 2.5%
**Biggest drop-offs:** Landing → Signup (68%), Onboarding → Activated (63%)

Step 3: Diagnose Drop-offs

For each significant drop-off:

### Drop-off: [Step A] → [Step B] ([%] drop)
**Hypotheses:**
1. [Reason — e.g., "Form is too long"] → Evidence: [Data/research]
2. [Reason] → Evidence: [Data]

**Recommended intervention:**
- [What to test + expected impact]

Step 4: Prioritize Improvements

| Leaky Step | Drop-off % | Potential Lift | Effort | Priority |
|-----------|-----------|---------------|--------|----------|
| [Step] | [%] | [Est. users saved] | [S/M/L] | [1/2/3] |

Quality Rubric

Dimension	0	1	2
Funnel Definition	Not defined	Steps listed	Steps + events + clear definitions
Data Quality	Estimated	Some real data	Full tracking with reliable data
Diagnosis	"Users leave"	Drop-offs quantified	Quantified + hypotheses + evidence
Action	"Fix the funnel"	Interventions listed	Prioritized by impact/effort

References

Related Skills

skills/growth/activation-optimization/SKILL.md — Activation funnel deep-dive
skills/growth/ab-test-design/SKILL.md — Test funnel interventions
skills/growth/growth-model/SKILL.md — Funnel drives growth model

Skill type: Component Domain: Analytics & Metrics

---name: funnel-analysisdescription: Build and analyze conversion funnels — identify drop-off points, diagnose conversion blockers, and design interventions. Covers funnel types, analysis methods, and common misinterpretations.---## PurposeBuild and analyze conversion funnels to identify **where users drop off, why they leave, and what to fix** — turning raw event data into prioritized improvement campaigns.---## Application### Step 1: Define the Funnel```markdown## Funnel: [Name — e.g., "Trial to Paid"]| Step | Event | Definition ||------|-------|-----------|| 1 | [Landing page visit] | [User arrives on landing page] || 2 | [Signup started] | [User clicks "Start trial"] || 3 | [Signup completed] | [User completes registration] || 4 | [Onboarding started] | [User begins setup] || 5 | [Activated] | [User completes activation event] || 6 | [Converted] | [User starts paid subscription] |```### Step 2: Measure Conversion```markdown| Step | Users | Conv. Rate | Drop-off ||------|-------|-----------|---------|| Landing page | 10,000 | — | — || Signup started | 3,200 | 32% | 68% || Signup completed | 2,400 | 75% | 25% || Onboarding | 1,800 | 75% | 25% || Activated | 670 | 37% | 63% || Converted | 252 | 38% | 62% |**Overall funnel conversion:** 2.5%**Biggest drop-offs:** Landing → Signup (68%), Onboarding → Activated (63%)```### Step 3: Diagnose Drop-offsFor each significant drop-off:```markdown### Drop-off: [Step A] → [Step B] ([%] drop)**Hypotheses:**1. [Reason — e.g., "Form is too long"] → Evidence: [Data/research]2. [Reason] → Evidence: [Data]**Recommended intervention:**- [What to test + expected impact]```### Step 4: Prioritize Improvements```markdown| Leaky Step | Drop-off % | Potential Lift | Effort | Priority ||-----------|-----------|---------------|--------|----------|| [Step] | [%] | [Est. users saved] | [S/M/L] | [1/2/3] |```---## Quality Rubric| Dimension | 0 | 1 | 2 ||-----------|---|---|---|| **Funnel Definition** | Not defined | Steps listed | Steps + events + clear definitions || **Data Quality** | Estimated | Some real data | Full tracking with reliable data || **Diagnosis** | "Users leave" | Drop-offs quantified | Quantified + hypotheses + evidence || **Action** | "Fix the funnel" | Interventions listed | Prioritized by impact/effort |---## References### Related Skills- `skills/growth/activation-optimization/SKILL.md` — Activation funnel deep-dive- `skills/growth/ab-test-design/SKILL.md` — Test funnel interventions- `skills/growth/growth-model/SKILL.md` — Funnel drives growth model---**Skill type:** Component**Domain:** Analytics & Metrics

Frequently asked questions

Funnel Analysis