---
title: Plan and Launch Experiments
description: >-
  Use Datadog Experiments to measure the causal relationship that new
  experiences or features have on user outcomes.
breadcrumbs: Docs > Experiments > Plan and Launch Experiments
---

# Plan and Launch Experiments

{% callout %}
# Important note for users on the following Datadog sites: app.ddog-gov.com

{% alert level="danger" %}
This product is not supported for your selected [Datadog site](https://docs.datadoghq.com/getting_started/site). ().
{% /alert %}

{% /callout %}

## Overview{% #overview %}

Use Datadog Experiments to measure the causal relationship that new experiences and features have on user outcomes. Datadog Experiments uses [Feature Flags](https://docs.datadoghq.com/getting_started/feature_flags/) to randomly allocate traffic between two or more variations, using one of the variations as a control group.

This page walks you through planning and launching your experiments.

## Setup{% #setup %}

To create, configure, and launch your experiment, complete the following steps:

### Step 1 - Create your experiment{% #step-1---create-your-experiment %}

1. Navigate to the [Experiments](https://app.datadoghq.com/product-analytics/experiments) page in Datadog Product Analytics.
1. Click **+ Create Experiment**.
1. Enter your experiment name and hypothesis.

{% image
   source="https://datadog-docs.imgix.net/images/product_analytics/experiment/exp_create_experiment.ef24f4d39ac8d2f0e7eda184800fcd8b.png?auto=format"
   alt="The experiment creation form with fields for experiment name and hypothesis." /%}

### Step 2 - Add metrics{% #step-2---add-metrics %}

After you have created an experiment, add your primary metric and optional guardrails. See [Defining Metrics](https://docs.datadoghq.com/experiments/defining_metrics) for details on how to create metrics.

{% image
   source="https://datadog-docs.imgix.net/images/product_analytics/experiment/exp_decision_metrics1.adb314dd2ba6b8a0bb8a0f32aab8e56f.png?auto=format"
   alt="The metrics configuration panel with options for primary metric and guardrails." /%}

#### Add a sample size calculation (optional){% #add-a-sample-size-calculation-optional %}

After selecting your experiment's metrics, use the optional sample size calculator to determine how small of a change your experiment can reliably detect with your current sample size.

1. Select the **Entrypoint Event** of your experiment. This specifies *when* in the user journey they will be enrolled into the test.
1. Click **Run calculation** to see the [Minimum Detectable Effects](https://docs.datadoghq.com/experiments/minimum_detectable_effect) (MDE) your experiment has on your metrics. The MDE is the smallest difference you can detect between your experiment's variants.

{% image
   source="https://datadog-docs.imgix.net/images/product_analytics/experiment/exp_sample_size.faf248846e4c5354a01db5484c0169dd.png?auto=format"
   alt="The Sample Size Calculator modal with the Entrypoint Event dropdown highlighted." /%}

### Step 3 - Launch your experiment{% #step-3---launch-your-experiment %}

After specifying your metrics, you can launch your experiment.

1. Select a feature flag that captures the variants you want to test. If you have not yet created a feature flag, see the [Getting Started with Feature Flags](https://docs.datadoghq.com/getting_started/feature_flags/) page.

1. Click **Set Up Experiment on Feature Flag** to specify how you want to roll out your experiment. You can either launch the experiment to all traffic, or schedule a gradual rollout.

{% image
   source="https://datadog-docs.imgix.net/images/product_analytics/experiment/exp_feature_flag.1b2f6468d4beeb4f4f45fd4d17c726dc.png?auto=format"
   alt="Set up an experiment on a Feature Flag." /%}

## Next steps{% #next-steps %}

1. **[Defining metrics](https://docs.datadoghq.com/experiments/defining_metrics)**: Define the metrics you want to measure during your experiments.
1. **[Reading Experiment Results](https://docs.datadoghq.com/experiments/reading_results)**: Review and explore your experiment results.
1. **[Minimum Detectable Effects](https://docs.datadoghq.com/experiments/minimum_detectable_effect)**: Choose appropriately sized MDEs.

## Further reading{% #further-reading %}

- [Make data-driven design decisions with Product Analytics](https://www.datadoghq.com/blog/datadog-product-analytics)
- [Defining Experiment Metrics](https://docs.datadoghq.com/experiments/defining_metrics)