LS Recommend is a tool in LS Central that was developed by LS Retail to enable companies to recommend products to their consumers based on their purchase history.
LS Recommend provides item and user based recommendation that can be displayed in the LS Central POS or printed on the slip. LS Recommend provides an interface on the Azure Cognitive Services Recommendations API with addition of LS Central specifications.
The recommendation engine is based on items and sales history. The sales history can be user-based where the user would be a member or a customer.
Recommendation can be given based on an item or a user, or both. There are three options available:
- Item to basket: recommends items based on items in a shopping basket. Note that the basket can only contain one item.
- Item to member or customer: recommends items based on a member’s or customer’s purchase history.
- Item to basket with member or customer: recommends items based on items in a shopping basket, and on a member’s or customer’s purchase history.
If there is no sales history available for the user, the recommendation is based on the items in his or her basket.