{ "sections": [ "title", "description", "fields", "usage" ], "title": "EngagementSignalMetric - Data API", "description": "Represents a measurable quantity that’s derived from an engagement signal, such as the sum of revenue or a count of clicks. Use this object to track user engagement for A/B tests, machine learning model training, and attribution configurations. This object is available in API version 62.0 and later.", "fields_columns": [ "type", "properties", "description", "relationship_name", "relationship_type", "refers_to" ], "fields": { "AggregateFunction": { "type": "picklist", "properties": "Defaulted on create, Filter, Group, Nillable, Restricted picklist, Sort", "description": "Defines the type of calculation used on the metric field. Possible values are: Avg Count Distinct Select Sum The default value is Count." }, "EngagementSignalId": { "type": "reference", "properties": "Create, Filter, Group, Sort", "description": "Represents the ID of the engagement signal that’s associated with the metric. This field is a relationship field.", "relationship_name": "EngagementSignal", "relationship_type": "Master-detail", "refers_to": "EngagementSignal (the master object)", "required": true }, "IsRemote": { "type": "boolean", "properties": "Defaulted on create, Filter, Group, Sort", "description": "Indicates if the engagement signal metric object is owned by a different org in Data 360. The default value is false." }, "LastReferencedDate": { "type": "dateTime", "properties": "Filter, Nillable, Sort", "description": "Timestamp that indicates the last time the engagement signal metric was referenced by the current user." }, "LastViewedDate": { "type": "dateTime", "properties": "Filter, Nillable, Sort", "description": "Timestamp that indicates the last time the current user viewed the engagement signal metric record." }, "Name": { "type": "string", "properties": "Filter, Group, idLookup, Sort", "description": "Text label that identifies the engagement signal metric.", "required": true } }, "usage": "These derived metrics serve as the core unit of measurement across the personalization platform. Use them to train machine learning models, measure performance in A/B tests, track outcomes in attribution models, and define custom objectives or compound metrics." }