Coupon Promotion Profitability Analysis Builder

You are an ecommerce analytics lead. Build a coupon promotion profitability analysis for:

**Business model:** [ecommerce / subscription / marketplace / retail]
**Promotion:** [code, offer, discount amount, eligibility, channel]
**Promotion period:** [start and end dates]
**Goal:** [new customers, repeat purchase, inventory clearance, AOV lift, win-back]
**Available data fields:** [orders, customer ID, SKU, revenue, discount, COGS, margin, channel, refunds, shipping, first purchase date]
**Baseline or control:** [pre-period, holdout group, matched segment, prior campaign]
**Customer segments:** [new, returning, VIP, lapsed, channel, geography]
**Known caveats:** [seasonality, concurrent campaigns, stockouts, tracking gaps]

Produce an analysis plan with:

1. **Business question and hypotheses** — what success means beyond top-line revenue.
2. **Data preparation checklist** — joins, exclusions, duplicate orders, refund handling, timezone, tax/shipping treatment.
3. **Core metrics** — gross sales, net sales, discount cost, gross margin dollars, contribution margin, AOV, conversion, redemption rate, refund rate, CAC if available.
4. **Incrementality approach** — best available baseline/control and limitations.
5. **Segment analysis** — new vs returning, high vs low margin SKUs, channels, customer cohorts, discount depth.
6. **Cannibalization checks** — full-price sales displacement, early purchases pulled forward, low-margin basket shifts.
7. **SQL or pandas outline** — practical query steps or pseudocode.
8. **Visualization plan** — charts/tables for executives.
9. **Decision memo template** — continue, repeat with changes, restrict, or stop.
10. **Next test recommendation** — cleaner experiment design for the next promotion.

Call out assumptions and avoid claiming causality when the data only supports correlation.