# Funnel Analysis

> Use to diagnose drop-off in an acquisition or activation funnel. Produces step-by-step conversion rates, identifies the single biggest leak, hypothesizes causes, and recommends one experiment to run. Always declares assumptions and data source.

- Skill: `shyamw-cloud/funnel-analysis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add shyamw-cloud/funnel-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/shyamw-cloud/funnel-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: shyamw-cloud (https://skillmd.com/u/shyamw-cloud)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/shyamw-cloud/funnel-analysis

---


# funnel-analysis

The point of a funnel is not to celebrate the top number — it's to find the **single biggest leak** and fix it.

## Inputs to gather

- **The funnel definition** — ordered list of events (e.g. visit → signup → activate → paid).
- **Window** — the date range (typically last 30 days).
- **Segment** — all users? a cohort? a channel?
- **Data source** — PostHog, Mixpanel, Amplitude, GA4, custom SQL.

## Method

1. Pull conversion at each step.
2. Compute step-to-step rates and the overall rate.
3. Identify the step with the **lowest conversion rate**, not the lowest absolute count.
4. Compare that step's rate to industry benchmark (if known) and to last period.
5. Hypothesize 3 causes. Rank them by likelihood × ease-to-test.
6. Recommend one experiment.

## Output format

```
## Funnel
| Step | Users | Step-to-step | Cumulative |
|---|---|---|---|
| Visit | 12,400 | 100% | 100% |
| Signup | 1,488 | 12.0% | 12.0% |
| Activate | 446 | 30.0% | 3.6% |
| Paid | 67 | 15.0% | 0.54% |

Window: <date range>
Segment: <segment>
Source: <data source>

## Biggest leak
**Activate → Paid (15.0%)** is the lowest step rate. Industry benchmark for B2B SaaS at this stage is 20-30%. We are 5-15 points below.

## Hypotheses
1. **Pricing-page friction** (high likelihood, easy to test) — users land on pricing without seeing ROI proof.
2. **Onboarding incomplete** (medium, medium) — users hit the paywall before reaching their "aha moment."
3. **Wrong ICP traffic** (medium, hard) — top-of-funnel is bringing tire-kickers.

## Recommended experiment
A/B test: insert a one-screen ROI calculator between activate and pricing.
Hypothesis: lifts Activate → Paid from 15% → 20%.
Sample size needed: ~3,500 users per variant for 95% confidence at 5pp lift.
Expected runtime: 4 weeks at current traffic.

## Caveats
- "Activate" is currently defined as <event>; some teams define it differently.
- Last week of data may be incomplete due to <reason>.
```

## Hard rules

- Always declare the funnel definition explicitly. "Activated" means nothing without the event.
- Never average step rates — multiply them for end-to-end conversion.
- Don't recommend an experiment without a sample-size estimate.
- If a step has < 200 users in the window, flag the rate as "low confidence."