UP-SELL - What else could be experimented with?

Marketing Alignment (MA)

Promoted Campaigns

Promote products or content in the target of active promoted campaigns

Visitor Journey Personalization (VJP)

Viewed Category, Brands & Landing Pages

Used Facets Values

Used Price Range

Used Higher Price Range

Previous Search(es)

Related Search(es)

Promote products matching the

• viewed top product-listing pages (category pages, brand pages, campaign landing pages, …)

• used facets values or price range (search / product listing filtering options)

• slightly higher price range than previously used

• prior searches (or related to the prior searches) of the visitor.

Customer Journey Personalization (CJP)

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)

Customer Journey Personalization (CJP)

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)

Visitor Journey Personalization (VJP)

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)

Visitor Journey Personalization (VJP)

Views > Low/High End

Promote products or content in the same Price Quadrant as previously viewed products.
Each product is connected to a price percentile according to its group (e.g.: category), lower percentiles (e.g.: <20%) are labeled Low-End while top percentiles (e.g.. >80%) are labeled High-End.

Customer Journey Personalization (CJP)

Purchases > Low/High End

Promote products or content in the same Price Quadrant as previously bought products.
Each product is connected to a price percentile according to its group (e.g.: category), lower percentiles (e.g.: <20%) are labeled Low-End while top percentiles (e.g.. >80%) are labeled High-End.

Customer Journey Personalization (CJP)

Purchases > Discovery Tags

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.

Customer Journey Personalization (CJP)

Wish-list > Products

Wish-list > Products Attributes

Wish-list > Products Discovery Tags

Wish-list > Products Defining Tags

Promote products

• currently in the wish-list of the visitor

• matching the values of attributes of products in the wish-list of the visitor

• matching the Discovery/Defining Tags of products in the wish-list of the visitor

See Discovery and Defining Tags definition above

Visitor Journey Personalization (VJP)

Basket > Products Attributes

Basket > Products Discovery Tags

Basket > Products Defining Tags

Promote products

• matching the values of attributes of products in the basket of the visitor

• matching the Discovery/Defining Tags of products in the basket of the visitor

See Discovery and Defining Tags definition above

Visitor Journey Personalization (VJP)

Views > Smart Bestsellers on Clustering

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

Customer Journey Personalization (CJP)

Purchases > Smart Bestsellers on Clustering

Best-selling trends within the Cluster the customer belongs.

Customer Clustering distributes all customers into clusters based on their purchase history