Metrics
A metric is a calculated, aggregated value that represents a business measure derived from underlying data. Metrics answer questions like “How many?”, “How much?”, “What is the total/average?” and are the core quantitative outputs shown in reports, dashboards, and notifications.
In short, a metric is a named calculation that summarizes data using an aggregation function.
Topics in this section:
Metrics Overview
The various areas and panels of the Define Metrics page are introduced in the following image:
Overview of the Define Metrics page in the Notification Wizard.
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Schema Panel—Data fields from all datasets are listed in this panel and can be dragged and dropped in various areas of the screen to be analyzed. The data type of each field is presented with an icon next to each. |
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Metrics Panel—Lists metrics that are available to the current notification. |
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Library Panel—Lists all metrics that are globally available to the current notification and other notifications. |
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Metrics Tab—The tab used for building a metric. |
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Metric Name—The area where your chart will appear and where you can add/change the name and description of the chart. |
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Metric Description—Describes what this measures. |
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Function—A dropdown menu where you can select an aggregation function: Sum, Average, Count, Minimum, Maximum. Note that the function available depends on the data type. For the data types Boolean, String and Date, only the functions Count, Minimum, and Maximum are available. |
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Field—Drag and drop a field from the Schema panel on the left to the Field area. |
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WHERE Conditions—These conditions allow you to filter the dataset before a metric is calculated. |
Drag fields from the Schema panel on the left into the blue or green box in the condition builder, choose an operator (such as =, >, <, BETWEEN, equals, not equals, contains), and enter a value or drag another field to compare against. Multiple conditions can be grouped using AND/OR logic to create complex expressions. The system validates each condition and prevents saving incomplete or invalid configurations. WHERE Conditions determine which rows contribute to the metric and therefore directly influence when a Conditional Notification is triggered.
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Derived Fields—Use this panel to create computed fields from one or more existing fields in the dataset. |
For more information, see Derived Fields.
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Derived Metrics—Use this panel to create metrics that operate on previously aggregated metrics. |
For more information, see Derived Metrics.
Metrics vs Raw Data
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Raw data (fields)
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Individual columns such as Entitlement ID, Account, Usage Count, Expiry Date
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Metric
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An aggregation over those fields, such as Count of entitlements, Total usage, Average consumption
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For example:
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Raw field: Remaining Copies |
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Metric: SUM(Remaining Copies) or COUNT(Remaining Copies) |
Filters and Slicing
Metrics can be:
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Filtered by dimensions (date, account, region, product) |
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Compared across time or categories |
Example: Count of Entitlements filtered by Country = Germany
Metrics Use Case Example
For example, you could create a metric that monitors "remaining entitlement copies" for a Scheduled Notification. You would create a metric by selecting the RemainingCopies field from line items and applied a count aggregation. The notification could be configured to trigger when the count of remaining copies is less than 10, which would notify the support team to take action.
The metric setup includes adding conditions, such as "remaining copies < 10," and the alert would send a CSV attachment with relevant entitlement details to recipients via email.
Building a Metric
If you selected Scheduled Notification as notification type, the Notification Wizard prompts you to define a metric on the Define Metrics page.
Revenera recommends that you familiarize yourself with the options on the Metrics tab by reading the Metrics Overview section before you attempt to build a metric.
To create a metric
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On the Define Metrics page, click +Add Metric. The Create New Metric panel is displayed. |
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In the Create New Metric panel, type a name for your metric and add a description. |
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Select an aggregation function: Sum, Average, Count, Minimum, Maximum. |
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Drag a desired field from the panel on the left side to the Field area. |
Tip:Type the name of the field into the Search box to quickly locate it.
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If desired, add conditions to your metric. |
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Click Create Metric to save your metric. |
Tip:To make this metric available for use in other notifications, save it to the Metric Library. For more information, see Saving Metrics to the Metrics Library .
Derived Fields
Derived Fields are new, computed fields created from one or more existing fields in the dataset. They allow you to perform mathematical operations—such as subtraction, division, or combining multiple values—to generate new values that support richer analytics.
Why Derived Fields Exist
Derived Fields serve these main purposes:
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To support more expressive conditions and metrics in Conditional Notifications
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Derived fields make conditional logic more flexible by enabling you to create fields that better match how you think about your data. A dataset may have Consumed Licenses, Remaining Licenses and Sold Licenses, but an alert might need a derived field:
Examples include:
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Percentage of Consumption: LINE_ITEMS.ConsumedCountDelta / LINE_ITEMS.LineItemSeatCount x 100 |
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Percentage Remaining: LINE_ITEMS.RemainingCopies / LINE_ITEMS.LineItemSeatCount x 100 |
These are classic computed expressions that don’t exist as stored columns but are essential for reporting and alerting, for example, when a certain threshold has been reached.
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To reduce repeated manual calculations and simplify UI logic
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Rather than repeatedly writing the same formula inside multiple metrics or conditions, you can define the calculation once as a Derived Field and then reuse it anywhere metrics or conditions are needed.
This also improves readability of complex condition sets in the notification builder.
Creating a Derived Field
Perform the following steps to create a derived field.
To create a derived field
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In the Notification Wizard on the left, click Metrics. |
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On the Define Metrics page, select the Derived Fields tab to open it. |
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Click +Add Derived Field. |
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In the Derived Fields panel, enter a Name for your field. |
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Drag fields from the Schema panel into the Expression area. Fields appear in a blue box. |
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To apply a function to a field, click the desired field in the Expression area. A list of functions is displayed. Click the desired function to apply it to the field. The box color of the field changes to purple. |
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Click the Operators to add them to your expression. Operators are displayed in a grey box. |
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To add a literal value, type the value in the the Add Literal Value text field, then click Add to add it to the expression. Literal values are displayed in a green box. |
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When you are finished, click Create Field to save the derived field. |
Derived Metrics
Derived Metrics are user-defined metrics created by applying mathematical operations to one or more existing metrics. They allow you to build advanced KPIs—such as ratios, indexes, or comparisons—by combining aggregated results instead of raw fields.
Derived Metrics differ from Derived Fields: derived fields operate on dataset fields before aggregation, while derived metrics operate on previously aggregated metrics.
Why Derived Metrics Are Useful
Derived Metrics are designed to help you express business logic that cannot be represented with a single aggregation. They are especially useful when:
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A business KPI requires multiple aggregated values
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For example:
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A base metric might compute Total Licenses Sold |
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Another might compute Total Licenses Consumed |
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A derived metric could then compute: |
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Consumption Ratio = Total Consumed / Total Sold |
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You need to reuse aggregated results without re-calculating them
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Instead of repeating calculations in multiple metrics or conditions, you can compute the measure once, then reuse the result in subsequent logic.
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Conditional Notifications depend on multi-step metric logic
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Some alert conditions rely on comparing different aggregated values. Derived metrics allow this without building complex expressions inside a single metric or condition.
Creating a Derived Metric
Perform the following steps to create a derived metric. These steps assume that you already have a metric that can be used as a basis for your derived metric.
To create a derived metric
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In the Notification Wizard on the left, click Metrics. |
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On the Define Metrics page, select the Derived Metrics tab to open it. |
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Click +Add Derived Metric. |
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In the Derived Metrics panel, enter a Name for your metric. |
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Build your expression: |
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Drag a metric from the Metrics or Library panel into the Expression area. The field appears in a blue box. |
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Click an Operator to add it to your expression. Operators are displayed in a grey box. |
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To add a number, type it in the Add Number text field, then click Add to add it to the expression. Numbers are displayed in a green box. |
Note:You must drag metrics, operators, and numbers into the Expression box in the exact sequence you want them to appear. After an item has been added, its position cannot be rearranged—however, you can remove any item at any time by clicking the x next to it.
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When you are finished, click Create Metric to save the derived metric. |
The derived metric is now available alongside standard metrics for:
Saving Metrics to the Metrics Library
When you create a metric in Analytics, you can save it to the Metric Library so that it can be reused across multiple conditional notifications. Saving a metric eliminates the need to recreate the same metric each time you configure a new notification and helps ensure consistency across notifications.
To save a metric
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Create your metric using the Metrics builder. |
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Click Save. This opens the Save Metric to Library panel, where you provide metadata for the metric before storing it in the library. |
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In the Save Metric to Library panel, specify the following information: |
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Name—A unique, descriptive name for the metric. |
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Description—A brief explanation of what the metric represents and how it is calculated. |
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Click Save to Library. |