Woo product cross sell analysis

woo-product-cross-sell-analysis

Purpose

Analyse WooCommerce completed orders to find product pairs that appear together most frequently. Surfaces natural cross-sell and bundle opportunities based on real purchase behavior. Read-only.

Prerequisites

• WooCommerce store with REST API enabled
• Consumer Key with Read scope
• Minimum WooCommerce version: 3.5.0

Parameters

Parameter	Type	Required	Default	Description
store_url	string	yes	—	Base URL of the WooCommerce store
consumer_key	string	yes	—	WooCommerce REST API consumer key (ck_...)
consumer_secret	string	yes	—	WooCommerce REST API consumer secret (cs_...)
dry_run	bool	no	false	No effect — read-only skill
format	string	no	human	Output format: human or json
date_after	string	yes	—	Start date (YYYY-MM-DD)
date_before	string	yes	—	End date (YYYY-MM-DD)
min_co_occurrences	int	no	5	Only report pairs appearing together at least this many times
top_n	int	no	20	Number of top product pairs to return

Authentication

WooCommerce uses OAuth 1.0a for HTTP and Basic Auth over HTTPS.

For HTTPS stores (recommended):

Authorization: Basic base64(consumer_key:consumer_secret)

For HTTP stores (development only): Use OAuth 1.0a — include oauth_consumer_key, oauth_nonce, oauth_signature, oauth_signature_method=HMAC-SHA1, oauth_timestamp, oauth_version=1.0

Never log or output consumer_key or consumer_secret values.

See docs/AUTHENTICATION.md for full setup instructions.

Safety

Read-only skill — no mutations are executed. Safe to run at any time.

Workflow Steps

Step 1 — Fetch completed orders in range

GET /wp-json/wc/v3/orders
  ?status=completed&after=<date_after>T00:00:00Z&before=<date_before>T23:59:59Z&per_page=100&page=1

For each order, extract the list of product_id values from line_items.

Step 2 — Build co-occurrence matrix

For each order with 2+ line items, generate all unique product ID pairs (combinations, not permutations). Increment the pair's counter.

for each order:
  product_ids = [item.product_id for item in order.line_items]
  for each pair (A, B) where A < B:
    co_occurrence[A][B] += 1

Step 3 — Filter and rank

Filter pairs with count < min_co_occurrences. Sort descending by co-occurrence count. Take top top_n.

Step 4 — Enrich with product names

GET /wp-json/wc/v3/products?include=<id1,id2,...>&per_page=100

Map product IDs to names.

Step 5 — Export

API Endpoints Used

GET  /wp-json/wc/v3/orders     — line items for co-occurrence analysis
GET  /wp-json/wc/v3/products   — product names for enrichment

Pagination Strategy

WooCommerce REST API uses page/per_page pagination (not cursor-based).

Standard pattern:

page = 1
while True:
  response = GET /endpoint?per_page=100&page=page
  process(response)
  if len(response) < 100: break
  page += 1

Maximum per_page is 100 for most endpoints. The X-WP-Total and X-WP-TotalPages response headers report totals. Always read X-WP-TotalPages on the first request to estimate job size.

Session Tracking

Claude MUST emit the following output at each stage. This is mandatory.

STARTUP:

╔══════════════════════════════════════════╗
║  SKILL: woo-product-cross-sell-analysis  ║
║  STORE: <store_url>                      ║
║  TIME:  <ISO-8601 UTC>                   ║
║  MODE:  READ-ONLY                        ║
╚══════════════════════════════════════════╝

PER-OPERATION (emit after each API call batch):

[N/TOTAL] <METHOD> <endpoint> → <result_count> records | params: <key>=<val>

COMPLETION (human format):

╔══════════════════════════════════════════╗
║  COMPLETE: woo-product-cross-sell-analysis║
║  RECORDS PROCESSED: <n>                  ║
║  OUTPUT: <filename>                      ║
╚══════════════════════════════════════════╝

COMPLETION (json format):

{
  "skill": "woo-product-cross-sell-analysis",
  "store": "<store_url>",
  "completed_at": "<ISO-8601>",
  "records_processed": <n>,
  "output_file": "<path>",
  "dry_run": false
}

Output Format

CSV filename: woo-product-cross-sell-analysis_<YYYY-MM-DD>_<YYYY-MM-DD>.csv Columns: product_a_id, product_a_name, product_b_id, product_b_name, co_occurrence_count, product_a_total_orders, product_b_total_orders, lift

Where lift = co_occurrence / (product_a_total_orders * product_b_total_orders / total_orders) — values > 1 indicate stronger-than-random association.

Error Handling

Error	Cause	Resolution
401 Unauthorized	Invalid credentials	Verify consumer_key and consumer_secret
403 Forbidden	Key lacks Read scope	Regenerate with Read scope
429 Too Many Requests	Rate limit	Wait 2 seconds and retry
Low pair counts	Date range too short or low order volume	Extend date_after/date_before range

Best Practices

• Use lift > 1.5 as the threshold for actionable cross-sell pairs — high co-occurrence alone can reflect popular products, not true affinity.
• Feed top pairs into WooCommerce product cross-sells via the product editor to surface recommendations at cart.
• Run quarterly — purchase patterns shift with seasonal inventory changes.