Group | Name | Short description | |
---|---|---|---|
1 | Previous Search(es) Related Search(es) | Promote products matching the prior searches (or related to the prior searches) of the visitor. | |
2 | Last Purchase > Often Bought After Last Purchase > Collaborative Filtering Bought After | Promote products often bought after the last purchase of the customer (first practice with statistics, second variant with AI Collaborative Filtering) | |
3 | Purchases > Often Bought By the Same Customer Purchases > Collaborative Filtering Bought By the Same Customer | Promote products often bought by the same customer (based on the purchase history of the customer) (first practice with statistics, second variant with AI Collaborative Filtering) | |
4 | Basket > Often Basketed Together Basket > Collaborative Filtering Basketed Together | Promote products often basketed together with products already in the basket of the visitor (first practice with statistics, second variant with AI Collaborative Filtering) | |
5 | Promote products or content in the same Price Quadrant as previously viewed products. | ||
6 | Promote products or content in the same Price Quadrant as previously bought products. | ||
7 | Purchases > Defining Tags | Promote products or content with Discovery Tags matching previously bought products. Each product gets a list of Discovery Tags representing the most common search terms used to find a product. Each product gets a list of Defining Tags representing which is a subset of the product attributes values that have been identified as important in the selection of a product. | |
8 | Wish-list > Products Wish-list > Products Attributes Wish-list > Products Discovery Tags Wish-list > Products Defining Tags | Promote products
See Discovery and Defining Tags definition above | |
9 | Basket > Products Attributes Basket > Products Discovery Tags Basket > Products Defining Tags | Promote products
See Discovery and Defining Tags definition above | |
10 | Best-selling trends within the Cluster the visitor is predicted to belong based on his prior product views. Customer Clustering distributes all customers into clusters based on their purchase history | ||
11 | Best-selling trends within the Cluster the customer belongs. Customer Clustering distributes all customers into clusters based on their purchase history |
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