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56 lines
2.5 KiB
JSON
56 lines
2.5 KiB
JSON
{
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"sections": [
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"title",
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"description",
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"fields",
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"usage"
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],
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"title": "EngagementSignalMetric - Data API",
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"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.",
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"fields_columns": [
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"type",
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"properties",
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"description",
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"relationship_name",
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"relationship_type",
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"refers_to"
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],
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"fields": {
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"AggregateFunction": {
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"type": "picklist",
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"properties": "Defaulted on create, Filter, Group, Nillable, Restricted picklist, Sort",
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"description": "Defines the type of calculation used on the metric field. Possible values are: Avg Count Distinct Select Sum The default value is Count."
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},
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"EngagementSignalId": {
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"type": "reference",
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"properties": "Create, Filter, Group, Sort",
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"description": "Represents the ID of the engagement signal that’s associated with the metric. This field is a relationship field.",
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"relationship_name": "EngagementSignal",
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"relationship_type": "Master-detail",
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"refers_to": "EngagementSignal (the master object)",
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"required": true
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},
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"IsRemote": {
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"type": "boolean",
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"properties": "Defaulted on create, Filter, Group, Sort",
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"description": "Indicates if the engagement signal metric object is owned by a different org in Data 360. The default value is false."
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},
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"LastReferencedDate": {
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"type": "dateTime",
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"properties": "Filter, Nillable, Sort",
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"description": "Timestamp that indicates the last time the engagement signal metric was referenced by the current user."
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},
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"LastViewedDate": {
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"type": "dateTime",
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"properties": "Filter, Nillable, Sort",
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"description": "Timestamp that indicates the last time the current user viewed the engagement signal metric record."
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},
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"Name": {
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"type": "string",
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"properties": "Filter, Group, idLookup, Sort",
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"description": "Text label that identifies the engagement signal metric.",
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"required": true
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}
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},
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"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."
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} |