Metrics
Dive into how to manage metrics and how you can use them for in-depth analysis.
To connect to a database other than Google Analytics you will need an
enterprise plan.
Contact sales
Introduction to Metrics
Metrics provide quantifiable measurements to gauge performance, behavior, and other essential information. These metrics facilitate in-depth analysis by providing insights that might not be easily visible from raw data.
Defining Metrics
Defining metrics involves specifying several parameters. Below is an overview of the parameters you’ll need:
Name
The reference name for the metric, which must be unique amongst all metrics.
Description
A detailed overview of the metric.Type
Type of metric (simple, ratio, cumulative, derived).Type Parameters
Specific parameters for each of the metric types.
To better understand the structure, here’s an illustrative example of a metrics specification:
metrics:
- name: order_total
description: Total orders processed.
type: simple
type_params:
measure: order_count
label: Total Orders
Supported Metric Types
We provides support for various metric types. Let’s explore them:
Simple metrics point directly to a measure. They can be perceived as a function that only accepts one measure as input.
Example:
metrics:
- name: cancellations
type: simple
type_params:
measure: cancellations_count
filter: |
{{ Dimension('order__value') }} > 100 and {{ Dimension('user__acquisition') }}
When creating metrics, ensure consistency across definitions. Avoid overlapping names and ambiguous definitions to ensure clarity.
Conclusion
Metrics are crucial for deriving actionable insights from your data. Understanding the different types of metrics and their definitions will help you create comprehensive data models.