Mail modules: Recommendation Strategies

This article provides a comprehensive overview of all mail modules currently available in the platform. Each module plays a specific role in powering personalized recommendations, merchandising strategies, and user experiences in your email channel. The documentation includes detailed descriptions, technical names, and key functionalities for each module. Please also find a Glossary at the end of this article.

Item modules: Contextual
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetPIMRelatedItemsMail	✓	Bought Together and more	Target Group, Category, Brand, etc.	Trending (visit)	✓	✓	✓	✓
GetPopularItemsInBrandMail	✓	Top in Brand		Popular Items	✓	✓	✓	✓
GetPopularItemsInCategoryMail	✓	Popular Items		Popular Items	✓	✓	✓	✓
GetSelectedItemsMail								✓
GetSimilarItemsMail	✓	Visited Together	Same category	Top in category > Popular	✓	✓	✓	✓
Item modules: Global
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetPopularItemsMail	✓	Trending and Popular			✓	✓	✓	✓
GetMerchandisingItemsMail	✓	Merchandising Products	Popularity & Discount				✓
Item modules: User
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetUserItemHistoryMail		User History		Popular Items		✓	✓	✓
GetUserCrossSellingItemsMail	✓	Look Alike Items		Favorite Category and Brand	✓	✓	✓	✓
GetUserItemRecommendationsMail	✓	Look Alike Items		Favorite Category > Popular	✓	✓	✓	✓
GetUserLookAlikeItemsMail	✓	Look Alike Items		Favorite Category > Popular	✓	✓	✓	✓

Content modules: Contextual
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetContentBasedOnItemMail	✓	Product to Content			✓	✓	✓	✓
GetContentBasedOnProductBrandMail	✓	Brand to Content		Popular Content	✓	✓	✓	✓
GetContentBasedOnProductCategoryMail	✓	Category to Content		Popular Content	✓	✓	✓	✓
GetItemsBasedOnContentMail	✓	Content to Products	Category and Brand	Top Viewed	✓	✓	✓	✓
GetSimilarContentMail	✓	Visited together	Same Category	Top Viewed	✓	✓	✓	✓
Content modules: Global
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetMerchandisingContentMail	✓	Merchandising Products	Popularity				✓
GetPopularContentMail*	✓	Trending and Popular	Overall Popular		✓	✓	✓	✓
* Trending: Reflects the change in popularity over the selected time period — indicating whether a product has become more popular. Content modules: User
Technical name	Personalized Rerank Opportunities	Candidate set	Explicit Schema Rules	Back-filling	Merchandising Boost	OData-filter	Content- / Product- / Category- / Brand-filter	FullInfo
GetUserContentHistoryMail		Recent History		Popular Content		✓	✓	✓
GetUserContentRecommendationsMail	✓	Similar Content		Top in Favorite Content	✓	✓	✓	✓

This glossary provides definitions for technical terms used in this article.

 

Definition: Products to be added at the end of the prioritized list of products when personalized recommendations aren’t available.

 

Candidate set
Definition: Defines the logic of the module - how the product selection is made, which data sources and filters are applied, and which attributes influence the final candidate list shown to the user. In Merchandising, this list (typically 50 products) is dynamic and behavior-based, forming the limited set within which boosting actions can take place.

 

Definition: Use this filter to remove item from the output based on a comma separated list.

 

Explicit Schema Rules
Definition: Module specific filtering. The rules are set up via a customized schema.

 

Definition: All mapped parameters from the item Schema are included in the API output. This enriches the recommendation data with additional item attributes.

 

Definition: Boosting products with a given value from the product Schema via Merchandising Boosted Campaigns.

 

Definition: Use this filter to remove groups of products from the output. Can be used on all mapped parameters from the product schema. Read more.