Goal
Suggest bundles based on sold order item patterns, listing names, variations, and order composition.
Recommendation Examples
- Items frequently purchased together.
- Seasonal theme bundles such as patriotic, Father's Day, dog mom, or bow/cookie-cutter sets.
- Physical full-set vs individual cutter bundles.
- Digital STL bundle opportunities.
Acceptance Criteria
- Detects multi-item orders and co-purchase patterns from order-item exports.
- Groups candidate bundles by listing theme, item name terms, variations, and buyer/order behavior.
- Produces structured bundle recommendations with evidence, confidence, expected benefit, and required user review.
- Separates digital-download bundle recommendations from physical-product bundle recommendations.
- Avoids inventing products not supported by listing/order evidence.
- Logs recommendation decisions for future performance comparison.
- Includes tests for multi-item orders, single-item orders, themed item names, and variation-based bundles.
Goal
Suggest bundles based on sold order item patterns, listing names, variations, and order composition.
Recommendation Examples
Acceptance Criteria