> ## Documentation Index
> Fetch the complete documentation index at: https://confidence-auth-testing.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Validate a New Metric

> Learn how to validate a newly created metric using exploratory analysis on a past experiment.

**Validate a New Metric**

Learn how to validate a newly created metric using exploratory analysis on a past experiment.

After creating a new metric, you should validate it to ensure it's calculating correctly and producing expected results. The best way to validate a metric is to test it against a previous experiment where you already know the outcome.

## Why Validate Metrics?

Validating metrics helps you:

* Confirm the metric calculates as expected
* Verify data joins and aggregations are correct
* Check that the metric responds to known treatment effects
* Inspect the underlying SQL for correctness
* Build confidence before using the metric in production experiments

## Before You Begin

* A completed experiment with known results
* A newly created metric that uses the same entity as the experiment
* Access to create explorations

## Validate Your Metric

**1. Select a past experiment**

Choose an experiment that:

* Has already completed and produced results
* Uses the same entity as your new metric

Navigate to the experiment's page in Confidence.

**2. Create a new exploration**

1. Go to the **Explorations** section in the right sidebar
2. Click **+** to create a new exploration
3. Give it a descriptive name like "Validate \[Metric Name]"

**3. Add your new metric**

1. Click **Add metric** to open the metric selection dialog
2. Select the checkbox next to your newly created metric
3. Click **Add metrics** to add it to the exploration
4. Click **Calculate** to start the analysis

> [!NOTE]
>
> You can only select metrics that use the same entity configured for the experiment.

**4. Add dimensions (optional)**

If you want to validate how your metric behaves across different segments:

1. Click **Add dimension** next to your metric
2. Select relevant dimensions from dimension tables
3. This helps you verify the metric works correctly across different user segments

**5. Review the results**

Once the calculation completes, examine the results:

* **Check the values**: Do the metric values look reasonable?
* **Compare to expectations**: If you know the experiment outcome, does your metric show similar patterns?
* **Review dimensions**: Do dimensional breakdowns make sense?

**6. Inspect the SQL**

If you need to debug the calculation itself, you can inspect the SQL query that was used to calculate the metric. To do this:

1. Find the status indicator showing the query job status
2. Click on the status to view details
3. Review the generated SQL query

> [!TIP]
>
> With Warehouse Native, you can copy the SQL and run it directly in your data warehouse to investigate further if needed.

**7. Document your findings**

Write a conclusion in the exploration describing:

* What you were validating
* Whether the metric behaves as expected
* Any issues discovered and how you resolved them
* Confirmation that the metric is ready for production use

This documentation helps others understand the validation process.

## Common Validation Checks

When reviewing your metric results, check for:

### Data Volume

* Does the metric produce results?
* Is the sample size similar to other metrics on this experiment?

### Treatment Effect Direction

* If the experiment had a positive effect, does your metric show that?
* Does the magnitude seem reasonable?
* Do confidence intervals make sense?

### Dimensional Consistency

* Do dimension breakdowns align with known patterns?
* Are there any segments with suspiciously different results?

### SQL Validation

* Are aggregations (SUM, AVG, COUNT) applied correctly?
* Are filters applied correctly?

## Related Resources

> **[Create a Metric](/docs/capabilities/metrics/create-metric.md)**
>
> Learn how to create metrics in Confidence

> **[Exploration](/docs/capabilities/experiments/exploration.md)**
>
> Understand how explorations work

> **[Explore Results](/docs/capabilities/experiments/explore-results.md)**
>
> Detailed guide on using the exploration feature

> **[Metrics Reference](/docs/capabilities/metrics/metrics.md)**
>
> Technical reference for metrics