Frequently Bought Together
Let real buying patterns inform your product recommendations.
Customers may benefit from a complementary product they have not found yet. Keeping those suggestions relevant becomes harder as your catalog and buying patterns change.
This recommendation engine looks at recent order history to identify products that frequently appear in the same purchase. It uses those pairings to provide cross-sell suggestions through a storefront widget.
The analysis uses a rolling period of orders, and common suggestions can use prepared wording for a quick response.
The order-history window, presentation, and recommendation wording could be adapted to your catalog and the shopping experience you want to create.
- Product pairings based on actual orders
- Recommendations informed by a rolling history window
- Storefront suggestions for complementary items
- Prepared wording for common recommendation cases
These are example builds for live stores. To scope a version around your products, team, and processes, start a brief.
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