Overview

Event Effect Analysis measures the real financial impact of a specific event — BFCM, a launch, a flash sale — by separating gross event-window revenue from truly incremental revenue with a disclosed baseline and a multi-week pull-forward measurement. You get a true event ROAS grounded in explicit counterfactual math, not platform ROAS.

What it does

• Baseline construction — 4-week trailing average with YoY seasonal adjustment.

• Gross vs incremental — real lift separated from what you'd have earned anyway.

• Pull-forward measurement — 4–8 weeks after, to catch borrowed demand.

• Per-platform spend — incremental spend attributed correctly.

• True event ROAS — with the counterfactual math shown.
  
  

How to use it

1. Connect Shopify and ad platforms.

2. Name the event and its window.

3. Shadow builds the baseline and measures incremental lift.

4. Get true event ROAS — with pull-forward accounted for.

Run it in-app or from Claude / ChatGPT via the Shadow MCP.

What it needs

Shopify plus ad-spend data spanning the event and the weeks around it.

What you get

A true-event-ROAS read: baseline, gross vs incremental revenue, pull-forward effect and per-platform spend.

Not the right skill when…

• You want ongoing channel truth → use Incrementality, instead

• You want a period recap → use Performance Report, instead

• You want to diagnose a metric → use Root-Cause Analysis, instead