Choosing a metric type | LaunchDarkly

Overview

The topics in this category help you understand the different types of LaunchDarkly metric so you can choose the correct metric for an experiment or guarded rollout.

You can use any of the metric event types to create conversion metrics, which aggregate and analyze events when an end user takes an action based on a feature flag they encounter. You must use custom events to create numeric metrics, which measure and analyze numerical values against a baseline that you set.

You can use any metric types to create an A/B experiment or A/A test, or to use as a release guardrail in a guarded rollout or release policy. You can add certain conversion metrics to a funnel metric group for use in experiments, guarded rollouts, or release policies.

This table includes examples of different different metric types and their common randomization units, and shows which metrics can be used experiments, funnel metric groups, and guarded rollouts:

Metric type	Example measurement	Example uses
Page viewed conversion	How many times do end users view a blog post? Example randomization unit: `user`	A/B experiment Funnel metric group Guarded rollout
Clicked or tapped conversion	How often do customers click a “Save” button? How many times do customers click on a link? When is the best point during a process to display a sign-up invitation? Example randomization unit: `user`	A/B experiment Funnel metric group Guarded rollout
Custom conversion count	How many purchases did a customer make? How many times per quarter do customers contact Support? Example randomization unit: `user` or `organization`	A/B experiment Guarded rollout
Custom conversion binary	Do customer searches call a particular service? Do customer payments succeed? Do customers contact customer service within a set period of time? Do customers renew their contract within 30 days? Does this process generate an error? Example randomization unit: `user` or `organization`	A/B experiment Funnel metric group Guarded rollout
Custom numeric	How much do customers spend per transaction in my store? How much do customers spend in total? How many items do customers purchase per transaction? How many items do customers purchase total? How much time do customers spend on a page? How long does it take for a server to respond to a request? How long until the time to first byte (TTFB)? Example randomization unit: `user`, `guest`, or `request`	A/B experiment Guarded rollout

You should choose a metric type that correctly measures the effect of a change on your customers or codebase. If you are unsure of what metric type to use, begin by determining what kind event you are trying to measure. For additional examples of common metrics and how to configure them, read Example metrics.

When you create a metric, you must also decide how you want to handle its metric and unit analysis. To learn more, read Metric aggregation and analysis.

The following sections describe how to create each metric type: