shopify-admin-frequently-bought-together

To find products frequently bought together, this Skill mines Shopify order line items using read-only GraphQL queries to compute support, confidence, and lift for product pairs. It outputs a ranked CSV of cross-sell and bundle candidates based on actual purchase co-occurrence.

The best way to identify cross-sell bundles is by calculating directional confidence and lift for product combinations. This approach surfaces both directional upsells and mutually reinforcing bundles from your historical order data rather than relying on guesswork.

Yes, you can analyze product co-occurrence over a configurable lookback window, such as 180 days. The analysis reads orders within that period to compute support and lift for product pairs and triplets to generate ranked bundle candidates.

This analysis uses read-only Shopify GraphQL queries to retrieve orders and products. It computes association metrics like support, confidence, and lift for product combinations without modifying your store data.

Bundle candidates are ranked by support, confidence, and lift metrics. The results are exported as a CSV file containing a ranked list of high-lift product pairs and optional triplets suitable for merchandising and email offers.