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  • Overview
  • Prerequisites
  • Warehouse native metric requirements
  • Create a warehouse native metric
Warehouse native

Warehouse native metrics

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Overview

This topic explains how to configure a warehouse native metric for use in an experiment. Warehouse native metrics are metrics that measure events stored in an external warehouse, such as Snowflake.

Prerequisites

Before you can create a warehouse native metric, you must configure a warehouse native Experimentation integration.

You should also create a new metric data source for the integration, which you can use to create a warehouse native metric. To learn more, read Metric data sources. You can optionally create a new data source when you create a new metric.

Warehouse native metric requirements

Warehouse native metrics must:

  • be any of custom conversion binary, custom conversion count, or custom numeric
  • use the “average” analysis method

Experiments that use warehouse native metrics cannot use:

  • clicked or tapped metrics
  • page viewed metrics
  • metric groups
  • LaunchDarkly hosted metrics that measure events from LaunchDarkly SDKs
  • metrics that use the percentile analysis method

Create a warehouse native metric

To create a warehouse native metric:

  1. Open the Data section and navigate to the Metrics list.
  2. Click Create metric. The “Create metric” dialog appears.
  3. Click Warehouse native.
  4. Select an existing data source from Metric data source, or click + Create to create a new data source.

Selecting a data source for a warehouse native metric.

Selecting a data source for a warehouse native metric.
  1. Finish creating the metric by continuing the procedure as described in custom conversion binary, custom conversion count, or custom numeric.

You can now create an experiment by selecting this metric.