# Experiment goals

> When you create an experiment, you can set a goal that describes the business outcome you want to test, such as higher revenue or lower discount spend. Each goal maps to a primary metric that defines how Talon.One evaluates the results.

> For the complete documentation index, see [llms.txt](https://docs.talon.one/llms.txt).

For example, imagine you want to lower your discount spend while maintaining your sales
volume. You can test a smaller discount against your current one and set a goal to
optimize discounts. The experiment results then show which variant keeps sales steady at
the lower cost. You can then
[create a campaign from the winning variant](/docs/product/campaigns/experiments/create-campaigns-from-experiments.md)
to make the most of your discount budget.

## Goal types and primary metrics

You can
[set or edit a goal](/docs/product/campaigns/experiments/create-experiments#set-or-edit-an-experiment-goal)
on the **Goal** page any time before you activate the experiment.

To set a goal, select one of the following goal types:

| Goal type | What it tests | Primary metric |
| --- | --- | --- |
| **Maximize revenue** | Which [effect](/docs/product/rules/effects/overview) drives a higher order value. | **Gross average order value (AOV)** |
| **Optimize discounts** | Which effect maintains sales with lower discounts. | **Net average order value (AOV)** |
| **Maximize purchased items** | Which effect drives a higher number of units per order. | **Average units per order (UPO)** |
| **Other** | Any other goal. | None. Talon.One compares all metrics. |

By default, the **Maximize revenue** goal type is selected.

For a description of each primary metric, see
[Experiment metrics](/docs/product/campaigns/experiments/manage-experiments#experiment-metrics).

## Hypothesis

The **Hypothesis** field is optional, and its content does not affect which variant wins.
Use it to record the assumption you want to test, so you have a benchmark to measure your
results against when you evaluate the experiment.

For example: `A 10% discount on orders over $50 increases the net average order value
among new customers without reducing sales volume.`

## Goals and experiment results

Your goal decides the winning variant shown in the
[experiment dashboard](/docs/product/campaigns/experiments/manage-experiments#evaluate-experiment-results).
When your goal sets a primary metric, Talon.One determines the outcome from that metric
alone:

- If one variant reaches statistical significance on the primary metric, Talon.One
  declares that variant the winning variant.
- If neither variant reaches statistical significance on the primary metric, the result is
  inconclusive.

Talon.One does not factor the other metrics into this decision, so a drop in one of them
does not make the result inconclusive. The
[evaluation table](/docs/product/campaigns/experiments/manage-experiments#understand-the-evaluation-table)
still shows all metrics, so you can review them before making a business decision.

When using the **Other** goal type, Talon.One compares all metrics to determine the
winning variant, in the same way as an experiment without a goal.

## Related pages

- [Create experiments](/docs/product/campaigns/experiments/create-experiments.md)
- [Manage experiments](/docs/product/campaigns/experiments/manage-experiments.md)