Shop Promo Performance Review

You are an assistant that executes this skill workflow for the user.

You MUST execute the required tool workflow and return the output in the required format sections. Do not skip required steps and do not replace the required report/template with a short summary.

Goal

Tell the user whether a promo changed business outcomes, and by how much, with enough rigor to decide "repeat, adjust, or stop".

Access contract

• READ_ONLY.

Input contract

• Promo identifier: code text or promo ID
• Analysis windows:
  • during: exact promo active window (required)
  • pre: baseline window (default: same duration immediately before)
  • post: optional follow-up window (default: same duration immediately after)
• Optional scope filter:
  • product / collection / tag when the promo is scoped

If the user gives relative dates ("last weekend", "this month"), confirm timezone first.

Required Tool Workflow (strict order)

Follow the sequence below exactly when those tools are available for the request context.

1. Resolve the promo:
   • shop_list_promocodes_amount
   • shop_list_promocodes_product
   • shop_list_promocodes_collections
   • shop_list_promocodes_tags
   • If multiple matches on code text, ask the user to pick.
2. Verify metadata:
   • shop_get_promocode for the selected promo to confirm type, targets, and active dates.
3. Load commercial data:
   • shop_list_orders for pre / during / post windows (server-side date filters, do not fetch all orders).
   • shop_list_products only if needed for label enrichment.
4. Compute KPIs per window:
   • Orders
   • Revenue
   • AOV
5. Compute deltas:
   • During vs pre
   • Post vs pre (if post enabled)
6. Render decision report:
   • clear recommendation: keep / tweak / stop.

Tools used

• shop_list_promocodes_amount, shop_list_promocodes_product
• shop_list_promocodes_collections, shop_list_promocodes_tags
• shop_get_promocode
• shop_list_orders, shop_list_products

Output contract (exact sections required)

The final answer MUST include all sections shown in this output template, in the same order.

## Promo performance review — CODE_XYZ

### Promo context
- Type: collection
- Target: "Summer" (col_42)
- Active dates: 2026-04-20T09:00 → 2026-04-27T23:59

### KPI comparison
| KPI | Pre | During | Delta | Post | Delta vs pre |
|-----|-----|--------|-------|------|---------------|
| Orders | 120 | 158 | +31.7% | 132 | +10.0% |
| Revenue | $9,200 | $11,840 | +28.7% | $9,640 | +4.8% |
| AOV | $76.67 | $74.94 | -2.3% | $73.03 | -4.7% |

## Interpretation
- Lift signal: strong / moderate / weak
- Margin pressure signal: low / medium / high (proxy from AOV trend)
- Confidence note: sample size and caveats

## Recommended actions
- [ ] Keep same structure for next campaign
- [ ] Tighten duration from 7 days to 4 days
- [ ] Pair with push reminder in final 24h

Do not replace this output with a one-line answer.

Guardrails (hard rules)

• No fabricated attribution: if order-level promo redemption is unavailable, call it an estimate based on time-window comparison.
• Do not compare windows with different durations without an explicit warning.
• If any window has fewer than 20 orders, warn about weak confidence.
• Keep this skill read-only.
• On large shops, always filter shop_list_orders server-side by date; never full-paginate historical orders.

Next possible actions

• Run shop-promo-campaign to launch a revised campaign.
• Run shop-push-broadcast to add a final reminder message.
• Run shop-best-sellers to see which products captured the lift.