Registry indexed
Read-only: identifies products with high single-purchase rates that could benefit from cross-sell pairing based on category and price affinity.
Read-only: identifies products with high single-purchase rates that could benefit from cross-sell pairing based on category and price affinity.
Source documentation, not instructions for this website. Review permissions before running any commands.
Finds products that are almost always purchased alone (single-item orders) and identifies potential cross-sell partners based on category affinity, price complementarity, and customer overlap. While frequently-bought-together finds existing patterns, this skill finds MISSING patterns — products that SHOULD be cross-sold but aren't. Read-only — no mutations.
shopify store auth --store <domain> --scopes read_orders,read_productsread_orders, read_products| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| store | string | yes | — | Store domain |
| days_back | integer | no | 180 | Order lookback window |
| solo_threshold | float | no | 70 | % of orders where product is bought alone to flag as "solo" |
| min_orders | integer | no | 10 | Minimum orders for a product to be analyzed |
| format | string | no | human | Output format: human or json |
ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.
OPERATION: orders — query
Inputs: query: "created_at:>='<NOW - days_back days>'", first: 250, select lineItems { product { id, title, productType, vendor }, quantity, originalTotalSet }, pagination cursor
Expected output: All orders with product data
For each product, calculate:
Flag products with solo rate ≥ solo_threshold as "cross-sell candidates"
OPERATION: products — query (enrichment)
Inputs: Product IDs for solo items and potential partners
Expected output: Product type, vendor, price, collections for affinity matching
For each solo product, suggest cross-sell partners:
# orders:query — validated against api_version 2025-01
query OrdersForCrossSell($query: String!, $after: String) {
orders(first: 250, after: $after, query: $query) {
edges {
node {
id
customer { id }
lineItems(first: 50) {
edges {
node {
product { id title productType vendor }
quantity
originalTotalSet { shopMoney { amount currencyCode } }
}
}
}
}
}
pageInfo { hasNextPage endCursor }
}
}
# products:query — validated against api_version 2025-01
query ProductEnrichment($ids: [ID!]!) {
nodes(ids: $ids) {
... on Product {
id
title
productType
vendor
priceRangeV2 {
minVariantPrice { amount currencyCode }
}
totalInventory
status
}
}
}
Claude MUST emit the following output at each stage. This is mandatory.
On start, emit:
╔══════════════════════════════════════════════╗
║ SKILL: Cross-Sell Opportunity Finder ║
║ Store: <store domain> ║
║ Started: <YYYY-MM-DD HH:MM UTC> ║
╚══════════════════════════════════════════════╝
After each step, emit:
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>
On completion, emit:
For format: human (default):
══════════════════════════════════════════════
CROSS-SELL OPPORTUNITY REPORT (<days_back> days)
Products analyzed: <n>
High solo-rate products: <n>
─────────────────────────────
TOP CROSS-SELL OPPORTUNITIES:
"<product A>" (solo rate: <pct>%, <n> orders)
→ Suggested partner: "<product B>" (same vendor, complementary type)
→ Price fit: $<main> + $<partner> = $<combined>
→ Potential AOV lift: +$<amount> per order
Revenue opportunity: $<total> (if <pct>% of solo orders add partner)
Output: cross_sell_opportunities_<date>.csv
══════════════════════════════════════════════
CSV file cross_sell_opportunities_<YYYY-MM-DD>.csv with columns:
product_id, product_title, total_orders, solo_orders, solo_rate, suggested_partner_id, suggested_partner_title, affinity_type, potential_aov_lift
| Error | Cause | Recovery |
|---|---|---|
THROTTLED | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| All multi-item orders | Store naturally has high cross-sell | Report as healthy — no action needed |
| Small catalog | Too few products for meaningful pairs | Suggest expanding catalog |
frequently-bought-together to see what IS working vs. what's missing.discount-ab-analysis to test a "buy X, get Y at 15% off" promotion.name: shopify-admin-cross-sell-opportunity-finder role: conversion-optimization description: "Read-only: identifies products with high single-purchase rates that could benefit from cross-sell pairing based on category and price affinity." toolkit: shopify-admin, shopify-admin-execution api_version: "2025-01" graphql_operations: - orders:query - products:query status: stable compatibility: Claude Code, Cursor, Codex, Gemini CLI
---
name: shopify-admin-cross-sell-opportunity-finder
role: conversion-optimization
description: "Read-only: identifies products with high single-purchase rates that could benefit from cross-sell pairing based on category and price affinity."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
- orders:query
- products:query
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
---
## Purpose
Finds products that are almost always purchased alone (single-item orders) and identifies potential cross-sell partners based on category affinity, price complementarity, and customer overlap. While `frequently-bought-together` finds existing patterns, this skill finds MISSING patterns — products that SHOULD be cross-sold but aren't. Read-only — no mutations.
## Prerequisites
- Authenticated Shopify CLI session: `shopify store auth --store <domain> --scopes read_orders,read_products`
- API scopes: `read_orders`, `read_products`
## Parameters
| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| store | string | yes | — | Store domain |
| days_back | integer | no | 180 | Order lookback window |
| solo_threshold | float | no | 70 | % of orders where product is bought alone to flag as "solo" |
| min_orders | integer | no | 10 | Minimum orders for a product to be analyzed |
| format | string | no | human | Output format: `human` or `json` |
## Safety
> ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.
## Workflow Steps
1. **OPERATION:** `orders` — query
**Inputs:** `query: "created_at:>='<NOW - days_back days>'"`, `first: 250`, select `lineItems { product { id, title, productType, vendor }, quantity, originalTotalSet }`, pagination cursor
**Expected output:** All orders with product data
2. For each product, calculate:
- Total orders containing this product
- Solo orders (product is the only item) vs. multi-item orders
- Solo rate = solo_orders / total_orders × 100
- Average order value when solo vs. when multi-item
3. Flag products with solo rate ≥ solo_threshold as "cross-sell candidates"
4. **OPERATION:** `products` — query (enrichment)
**Inputs:** Product IDs for solo items and potential partners
**Expected output:** Product type, vendor, price, collections for affinity matching
5. For each solo product, suggest cross-sell partners:
- Same vendor, different product type (complementary)
- Same product type, different price tier (good-better-best)
- Products bought by the same customer cohort in separate orders
- Price complementarity: partner price should be 20-50% of main product price (impulse add-on range)
## GraphQL Operations
```graphql
# orders:query — validated against api_version 2025-01
query OrdersForCrossSell($query: String!, $after: String) {
orders(first: 250, after: $after, query: $query) {
edges {
node {
id
customer { id }
lineItems(first: 50) {
edges {
node {
product { id title productType vendor }
quantity
originalTotalSet { shopMoney { amount currencyCode } }
}
}
}
}
}
pageInfo { hasNextPage endCursor }
}
}
```
```graphql
# products:query — validated against api_version 2025-01
query ProductEnrichment($ids: [ID!]!) {
nodes(ids: $ids) {
... on Product {
id
title
productType
vendor
priceRangeV2 {
minVariantPrice { amount currencyCode }
}
totalInventory
status
}
}
}
```
## Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
```
╔══════════════════════════════════════════════╗
║ SKILL: Cross-Sell Opportunity Finder ║
║ Store: <store domain> ║
║ Started: <YYYY-MM-DD HH:MM UTC> ║
╚══════════════════════════════════════════════╝
```
**After each step**, emit:
```
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>
```
**On completion**, emit:
For `format: human` (default):
```
══════════════════════════════════════════════
CROSS-SELL OPPORTUNITY REPORT (<days_back> days)
Products analyzed: <n>
High solo-rate products: <n>
─────────────────────────────
TOP CROSS-SELL OPPORTUNITIES:
"<product A>" (solo rate: <pct>%, <n> orders)
→ Suggested partner: "<product B>" (same vendor, complementary type)
→ Price fit: $<main> + $<partner> = $<combined>
→ Potential AOV lift: +$<amount> per order
Revenue opportunity: $<total> (if <pct>% of solo orders add partner)
Output: cross_sell_opportunities_<date>.csv
══════════════════════════════════════════════
```
## Output Format
CSV file `cross_sell_opportunities_<YYYY-MM-DD>.csv` with columns:
`product_id`, `product_title`, `total_orders`, `solo_orders`, `solo_rate`, `suggested_partner_id`, `suggested_partner_title`, `affinity_type`, `potential_aov_lift`
## Error Handling
| Error | Cause | Recovery |
|-------|-------|----------|
| `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| All multi-item orders | Store naturally has high cross-sell | Report as healthy — no action needed |
| Small catalog | Too few products for meaningful pairs | Suggest expanding catalog |
## Best Practices
- Products with 80%+ solo rate and high order volume are biggest AOV opportunities.
- Implement suggested pairs as "Customers also bought" or cart drawer recommendations.
- Cross-reference with `frequently-bought-together` to see what IS working vs. what's missing.
- Use with `discount-ab-analysis` to test a "buy X, get Y at 15% off" promotion.
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
69/100
Promising
Trust
64/100
Sandbox only
Audit
78/100
Needs review
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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