Experimentation Summary DMO
The Experimentation Summary DMO captures the overall summary of personalization experiments.
ssot__AbnExperimentationSummary__dlm
Experimentation Summary ID (Id__c
)
Field Name | Field API Name | Description | Data Type |
---|---|---|---|
Experiment | AbnExperimentId__c | The identifier for the experiment. | text |
Experiment Cohort | AbnExperimentCohortId__c | The identifier for the cohort that's assigned to the experiment. | text |
Metric Name | MetricName__c | The name of the engagement signal metric that the experiment measures. | text |
Metric Id | MetricId__c | The identifier for the engagement signal metric that the experiment measures. | text |
Experiment Analysis Status | ExperimentAnalysisStatus__c | The status of the experimentation data analysis. | |
Metric Type | ExperimentSummaryMetricType__c | The type of engagement signal metric that the experiment measures. | text |
Is Primary | IsPrimary__c | Indicates if the metric is a primary metric that's used to determine the winner of the experiment. | boolean |
Last Updated Date Time | LastUpdatedDateTime__c | The date and time when the experiment summary was last updated. | dateTime |
Assigned Participants Count | AssignedParticipantsCount__c | The number of participants assigned to the cohort that's assigned to the experiment. | number |
Metric Value | MetricValueNumber__c | The metric value measured as part of the experiment. | number |
Min Metric Value | MinMetricValueNumber__c | The lowest value of the metric recorded during the experiment. | number |
Max Metric Value | MaxMetricValueNumber__c | The highest value of the metric recorded during the experiment. | number |
Mean Metric Value | MeanMetricValueNumber__c | The average metric value recorded during the experiment. | number |
Variance | VarianceNumber__c | The statistical spread of metric values, calculated by taking the average of squared deviations from the mean. | number |
Credible Interval Lower | CredibleIntervalLowerNumber__c | The lower value of the Bayesian credible interval. The credible interval is the range of the posterior distribution that contains the configured percentage of probable values. | number |
Credible Interval Upper | CredibleIntervalUpperNumber__c | The upper value of the Bayesian credible interval. | number |
Probability To Beat Control | ProbabilityToBeatControlPercent__c | The probability of the cohort for the measured metric to win against the control. | number |
Probability To Beat All | ProbabilityToBeatAllPercent__c | The probability of the cohort for the measured metric to win against all the other cohorts. | number |
Signal Numerator Value | SignalNumeratorValueNumber__c | The numerator of MetricValueNumber if ExperimentSummaryMetricType is either RATE or AVG. | number |
Signal Denominator Value | SignalDenominatorValueNumber__c | The denominator of MetricValueNumber if ExperimentSummaryMetricType is either RATE or AVG. | number |