Persnl Rcmd Log DMO

Captures each inference event produced by the personalization recommendation engine — one record per ranked response generated for a given individual and context. Source data flows from the decisioning pipeline service, which emits the request context, candidate set, model response, and inference metadata. Downstream, machine learning training pipelines join these records with engagement logs to retrain contextual bandit models across different use cases such as product recommendations, offer treatment selection.

Object API Name: std__PersnlRcmdLogDmo__dlm
Category: Unassigned
Availability: Available in 262 and later versions
Primary Key Field: Id

• IndividualId has a FOREIGNKEY relationship with the Individual DMO Id field.
• PersonalizerId has a FOREIGNKEY relationship with the Personalizer DMO Id field.

• CandidateCount
• CandidateList
• cdp_sys_record_currency
• ContextAnchorEmbeddingTxt
• DataSourceId
• DataSourceObjectId
• Id
• IndividualId
• InternalOrganizationId
• ModelMetadata
• PersonalizationIdentifier
• PersonalizerId
• RecommenderType
• RequestDateTime
• ResponseCount
• ResponsePayloadTxt

• Field API Name: std__CandidateCount__c
• Data Type: DOUBLE
• Description: The total count of candidate items supplied as input to the contextual bandit model (Machine Learning model) for this inference request.

• Field API Name: std__CandidateList__c
• Data Type: TEXT
• Description: Serialized JSON list of candidate items supplied to the contextual bandit model (Machine Learning model) as input for reranking. Each candidate carries its identifier, catalog type, and a dynamic attribute set (relevance score, price and other per-use-case attributes).

• Field API Name: std__cdp_sys_record_currency__c
• Data Type: TEXT
• Description: System-generated metadata field that stores a 3-letter ISO currency code.

• Field API Name: std__ContextAnchorEmbeddingTxt__c
• Data Type: TEXT
• Description: Serialized JSON payload capturing the contextual anchors supplied to the model as input like the product the user is viewing.

• Field API Name: std__DataSourceId__c
• Data Type: TEXT
• Description: A unique, system-generated identifier for this record.

• Field API Name: std__DataSourceObjectId__c
• Data Type: TEXT
• Description: A unique, system-generated identifier for this record.

• Field API Name: std__Id__c
• Data Type: TEXT
• Description: System-generated unique identifier for this recommendation inference event record. Serves as the row-level primary key.

• Field API Name: std__IndividualId__c
• Data Type: TEXT
• Description: Reference to the Individual in whose context this recommendation was produced.

• Field API Name: std__InternalOrganizationId__c
• Data Type: TEXT
• Description: A unique, system-generated identifier for this record.

• Field API Name: std__ModelMetadata__c
• Data Type: TEXT
• Description: Serialized JSON payload capturing the metadata used by downstream training and analytics pipelines - exploitation version, MES context vectors, reward probabilities.

• Field API Name: std__PersonalizationIdentifier__c
• Data Type: TEXT
• Description: A system-generated UUID assigned to each personalization decision produced by the personalization pipeline. A single inbound request may target multiple personalization points on a page (for example, five different surfaces personalized in one call), and each point receives its own Personalization Id.

• Field API Name: std__PersonalizerId__c
• Data Type: TEXT
• Description: Identifier of the recommender (model configuration) that produced this inference, scoped to the tenant. Distinguishes inference events across different recommenders within the same tenant and allows training pipelines to narrow the dataset to the recommender being retrained.

• Field API Name: std__RecommenderType__c
• Data Type: TEXT
• Description: Classification of the kind of recommender that produced this inference event, such as objective-based or strategy-based recommenders. Allows training pipelines and analytics to group or filter events by recommender category for model evaluation and exploration/exploitation analysis.

• Field API Name: std__RequestDateTime__c
• Data Type: DATETIME
• Description: Timestamp at which the recommendation engine began processing this inference request.

• Field API Name: std__ResponseCount__c
• Data Type: DOUBLE
• Description: The total count of items returned by the contextual bandit model (Machine Learning model) in the response for this inference request.

• Field API Name: std__ResponsePayloadTxt__c
• Data Type: TEXT
• Description: Serialized JSON list of ranked items returned by the contextual bandit model (Machine Learning model) for this inference, including per-item dynamic attributes the model emits.