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CrossupsellSearchInput

Search criteria for filtering cross-sell and upsell recommendations.

Provides comprehensive filtering capabilities across recommendation data including source products, target products, recommendation types, subtypes, and date ranges. Results can be sorted and paginated for efficient data retrieval.

All filter fields are optional - if not provided, returns all accessible recommendations with default pagination settings.

input CrossupsellSearchInput {
  ids: [String!]
  productIdsFrom: [Int!]
  clusterIdsFrom: [Int!]
  productIdsTo: [Int!]
  clusterIdsTo: [Int!]
  types: [CrossupsellType!]
  subTypes: [String!]
  sortInputs: [CrossupsellSortInput!]
  page: Int
  offset: Int
  createdAt: DateSearchInput
  lastModifiedAt: DateSearchInput
}

Fields​

CrossupsellSearchInput.ids ● [String!] list scalar​

Filter recommendations by their unique identifiers.

Allows you to retrieve specific cross-sell/upsell recommendations when you know their exact IDs. Useful for bulk operations or when working with a predefined set of recommendations.

CrossupsellSearchInput.productIdsFrom ● [Int!] list scalar​

Filter recommendations by source product identifiers.

Find all recommendations that are triggered by any of the specified products. When customers view or interact with these products, the filtered recommendations will be suggested. Useful for analyzing what products are being recommended from specific source products.

CrossupsellSearchInput.clusterIdsFrom ● [Int!] list scalar​

Filter recommendations by source product cluster identifiers.

Find all recommendations that are triggered by any product within the specified clusters. This enables scalable filtering across multiple related products that share similar characteristics or categories.

CrossupsellSearchInput.productIdsTo ● [Int!] list scalar​

Filter recommendations by target product identifiers.

Find all recommendations that suggest any of the specified products. Useful for analyzing which source products or clusters are driving recommendations for specific target products, helping optimize product visibility and sales performance.

CrossupsellSearchInput.clusterIdsTo ● [Int!] list scalar​

Filter recommendations by target product cluster identifiers.

Find all recommendations that suggest products from any of the specified clusters. This enables analysis of cluster-level recommendation performance and helps optimize product grouping strategies.

CrossupsellSearchInput.types ● [CrossupsellType!] list enum​

Filter recommendations by their relationship types.

Allows filtering by one or more recommendation types to focus on specific kinds of product relationships:

  • ACCESSORIES: Complementary products that enhance the main product
  • ALTERNATIVES: Substitute products for comparison or when main product unavailable
  • OPTIONS: Upgrades, variations, or enhanced versions of the main product
  • PARTS: Replacement components, spare parts, or consumables
  • RELATED: Products commonly purchased together with the main product

Accepts one or more values from: [accessories, alternatives, options, parts, related]

CrossupsellSearchInput.subTypes ● [String!] list scalar​

Filter recommendations by their custom subtype classifications.

Allows filtering by one or more subtypes for more granular categorization within the main recommendation types. Common examples include:

  • "CHEAPER_ALTERNATIVE", "PREMIUM_ALTERNATIVE", "SIMILAR_FEATURES"
  • "ESSENTIAL", "OPTIONAL", "PREMIUM_ADDON"
  • "SIZE_VARIANT", "COLOR_VARIANT", "FEATURE_UPGRADE"
  • "REPLACEMENT", "CONSUMABLE", "MAINTENANCE"

CrossupsellSearchInput.sortInputs ● [CrossupsellSortInput!] list input​

Specify multiple sorting criteria for the recommendation results.

Each sort input defines a field and order direction. Results will be sorted by the first criteria, then by subsequent criteria for ties. This enables complex sorting like "sort by type ascending, then by creation date descending".

CrossupsellSearchInput.page ● Int scalar​

The page number for pagination of search results.

Used in combination with offset to control which subset of results to return. Page numbering starts at 1. Higher page numbers return later results in the sorted dataset.

Default value: 1, minimum value: 1

CrossupsellSearchInput.offset ● Int scalar​

The number of results to return per page.

Controls the page size for pagination. Larger values return more results per request but may impact performance. Smaller values provide faster responses but require more requests for large datasets.

Default value: 12, minimum value: 1, maximum value: 100

CrossupsellSearchInput.createdAt ● DateSearchInput input​

Filter recommendations by their creation date range.

Allows filtering by when recommendations were originally created in the system. Useful for analyzing recommendation creation patterns, finding recently added recommendations, or filtering by specific time periods.

CrossupsellSearchInput.lastModifiedAt ● DateSearchInput input​

Filter recommendations by their last modification date range.

Allows filtering by when recommendations were last updated or modified. Useful for tracking recent changes, finding stale recommendations, or analyzing recommendation maintenance patterns.

Member Of​

crossupsells query