Sorting

The Sort rule defines the order in which products are displayed once the base set (after filtering) has been defined. It determines which products are prioritized first within the recommendation list.

How it works

Each sorting rule is composed of:

Element	Description
Property	The product attribute used to rank products (e.g., price, stock, rating, booster_search_low, category, etc.).
Order	The direction of the sort: Ascending (lowest to highest) or Descending (highest to lowest).

Multiple sorting criteria can be combined to refine the order of results. The system applies them sequentially, from top to bottom.

Example:

1. Sort by booster_search_low (Descending)

2. Then by item_pageview_key (Descending)

The platform will first sort by the main criterion, then use the second one only to rank products with identical values in the first criterion.

Adding multiple sorts

You can add as many sorting levels as necessary using the Add a sort button. Each new sorting condition is applied in sequence after the previous one.

For example:

• Primary sort: booster_search_low (Descending)

• Secondary sort: price (Ascending)

• Tertiary sort: rating (Descending)

This allows fine-tuned ranking logic, balancing relevance, performance, and commercial priorities.

Properties available for sorting

The available properties depend on the product dataset connected to the catalog. Common examples include:

Property	Description	Typical Use
price	Product price	Show cheapest or most expensive first
stock	Available stock quantity	Prioritize in-stock items
rating	Average customer rating	Highlight top-rated products
booster_search_low	Internal ranking variable used for semantic or search-based boosts	Optimize by algorithmic relevance
item_pageview_key	Product view frequency	Promote most-viewed products
category	Product category	Group or sort within a specific type
active	Availability flag (true/false)	Prioritize active or sellable products

Combining filters and sorts

Sorting rules can be combined with filters to further refine product selection. For instance:

• Filter: stock > 0

• Sort: price Ascending, then rating Descending

This approach ensures only valid products are considered and ranked according to defined priorities.

Example use cases

• Sort by popularity and display top-performing items: item_pageview_key Descending

• Rank by price to create a “Low to High” experience: price Ascending

• Prioritize stock availability for operational efficiency: stock Descending

• Combine algorithmic scoring with merchandising logic: booster_search_low Descending, then price Ascending