Metrics
Metrics are the basis for measuring your business. They are times-series aggregations of data that can be defined inside of Push.ai or integrated using semantic layers such as the dbt Semantic Layer, Looker and Cube.
Features
- Define metrics in one place and use them across a variety of use-cases without the need to maintain defintions.
- Track historical results, see automated projections and compare them to business goals.
- Use pre-built calculations to quickly explore how metrics change over time.
Defining Metrics
Our metric builder allows teams to easily input metric definitions and dynamically generate the yml used to store them in dbt. We also include some best practice metadata so that Push.ai and other systems can better organize and deliver value using metrics. Below is the complete list of properties that are needed to make metrics.
Definition Types
- Metric Builder - The easiest way to define a metric. Select a table and the fields used to configure a metric.
- Custom SQL - A flexible solution with the ability to join tables, edit and paste in SQL from other sources.
- Derived Metric - Use existing metrics to define metrics with parent-child relationships, like average order value.
Definition Configuration
| Field | Description | Example | Required? |
|---|---|---|---|
| Table | The table used to calculate this metric | dim_customers | yes (no for derived metrics) |
| Calculation Type | The method of calculation that is applied to the expression | count_distinct | yes |
| Calculation Field | The expression to aggregate/calculate over | user_id | yes |
| Date Field | The time-based component of the metric | signup_date | yes |
| Dimensions | A list of dimensions to group or filter the metric by | [plan, country] | no |
| Filters | A list of filters to apply before calculating the metric | status = ‘active’ | no |
Properties
Metric properties define how a metric is calculated in Push.
| Field | Description |
|---|---|
| Goal Direction | Defines whether the business goal is to increase or decrease the metric. |
| Aggregation Properties | Configures whether this metric can be aggregated across the date dimension. |
| Metric Format | Configures whether a metric will display as a number, percent or currency when displayed. |
Derived Metrics
Derived metrics use existing metric definitions to calculate a new metric with a parent-child relationship. For example, Profit is a derived metric that can be calculating using the parent metrics of Revenue and Cost (profit = revenue - costs). Using derived metrics makes maintaining metric definitions easier by defining the supporting metrics in one definition and then having the derived metrics inherit any metric changes.
With derived metrics, dimensions are inherited. The dimensions available for derived metrics are the ones shared by all related metrics
Calculations
Calculations help us explore how metrics change over time. You are likely already familiar with them if you’ve used traditional Business Intellignece tools.
In Push.ai, calculations are used to compare metrics across time periods. Each calculation in Push.ai is associated with two time periods, a current period and a previous period. Individual calculations will be relevant depending on the use-case (e.g., you want to track something on a daily v. monthly cadence) or the nature of the business (e.g., you run an ecommerce business and order volume has a strong day-of-week seasonality).