Product recommendations
Product recommendations are generated using machine learning, product attributes, and customer behavior data.
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Recommendations fall into the following categories:
Buy it again
2 items
Complementary items
Suggested products that customers frequently buy together.
Product pairings
Products that pair well together can inspire customers to try new items.
Nutritious choices
Products with high nutritional content.
Replacement items
Instructions for when a customer's preferred product is unavailable.
Restock reminders
Restock reminders nudge customers to repurchase items from categories they buy regularly.