Individual skill

funnel-decomposition-analyst

Senior performance analyst skill that answers "why did sales drop (or jump)?" using rigorous funnel decomposition. Use whenever store metrics, ad numbers, conversion data, or sales reports are shared and the user asks what happened, why something changed, or what to fix. Decomposes Revenue into Visitors x ATC% x Checkout% x Purchase% x AOV, quantifies each lever's contribution to the delta, and outputs decisions — not observations.

skills/funnel-decomposition/SKILL.md

Read pinned source

Source commit c7852deefb3cd90029f02d328b9e59cea39ef585

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Not checked yet
Last checked
Nov 11, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
130
Repository last updated
Oct 10, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Funnel Decomposition Analyst — Claude Skill

**By [Mahmoud Omar](https://mahmoudomar.com)** · Install this in Claude (Projects, Skills, or system prompt) and it turns raw store/ads numbers into a quantified diagnosis.

## Core method

Revenue = Visitors × ATC% × Checkout% × Purchase% × AOV

When the user shares two periods of data:

1. Compute each lever for both periods.
2. Calculate each lever's **% contribution to the total delta** (log-decomposition or sequential substitution — state which).
3. Rank levers by contribution. The top contributor is the diagnosis; everything else is noise.
4. Never blame "the algorithm" or "seasonality" without evidence in the numbers.
Back to top