# Segment insights

> The Segment insights table, at the bottom of the experiment dashboard, breaks down your experiment results by pre-defined customer segments. Use it to find the customer groups where one variant outperforms the other for a specific metric. A variant that looks inconclusive overall can still be the winning variant for a specific segment, for example, customers with a high gross average order value.

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

:::note
The **Segment insights** table appears only after the experiment has collected enough
data. To learn more, see
[Read the Segment insights table](#read-the-segment-insights-table).
:::

Talon.One discovers these segments automatically and only shows those with high
confidence. When a variant performs better for a segment on one metric, confirm this with
a follow-up experiment targeting that segment, instead of discarding an inconclusive
experiment.

## Pre-defined segments

The pre-defined segments fall into three dimensions. A dimension is a session or customer
characteristic, split into segments such as low, medium, and high order value. The
dimensions are **Order value**, **Units per order**, and **Customer type**.

Only
[closed sessions](/docs/dev/concepts/entities/customer-sessions#customer-session-states)
with at least one effect applied are included, where each closed session represents one
order. For the **Customer type** dimension, an order is included only if it also has a
valid customer profile.

For the **Order value** and **Units per order** dimensions, Talon.One sorts orders into
low, medium, and high thirds. It uses the same cut-off points for both variants, so the
segments stay comparable. For **Order value**, it measures each order's value after any
returns.

The following table lists the segments in each dimension:

| Dimension | Segment | Definition |
| --- | --- | --- |
| Order value | Low average order value (AOV) | Orders in the bottom third by order value. |
| Order value | Medium average order value (AOV) | Orders in the middle third by order value. |
| Order value | High average order value (AOV) | Orders in the top third by order value. |
| Units per order | Low average units per order (UPO) | Orders in the bottom third by item count. |
| Units per order | Medium average units per order (UPO) | Orders in the middle third by item count. |
| Units per order | High average units per order (UPO) | Orders in the top third by item count. |
| Customer type | New customers | Customers with one completed order across the entire Application history. |
| Customer type | Returning customers | Customers with two or three completed orders across the entire Application history. |
| Customer type | Frequent customers (4+ orders) | Customers with four or more completed orders across the entire Application history. |

## Read the Segment insights table

Talon.One groups segment insights into tabs, one for each metric. A tab appears only when
at least one segment reaches high confidence for that metric, so fewer than three tabs can
appear. The number next to each tab shows the count of segments it contains. The tabs
cover the same three average metrics shown in the evaluation table:

- **Gross average order value (AOV)**
- **Net average order value (AOV)**
- **Average units per order (UPO)**

Within each tab, segments are sorted by confidence score, from highest to lowest. The
table includes the following columns:

| Column | Description |
| --- | --- |
| Segment | The name of the segment and the dimension it belongs to. |
| Confidence | The confidence score for the difference between the variants, displayed as a percentage. The score is calculated using Welch's t-test. |
| Variant A | The metric value for **Variant A**, followed by the number of orders in the segment. |
| Variant B | The metric value for **Variant B**, followed by the number of orders in the segment. |
| Difference (B vs A) | The difference between the two variants, displayed as a value and as a percentage. |
| Winning variant | The variant with the best score for the segment. |

:::note
Talon.One shows a segment only when it has enough data and statistical confidence. The
table can be missing segments, or appear entirely empty, for these reasons:

- **Low traffic**: The experiment has fewer than 100 orders per variant, or an individual
  segment has fewer than 100 orders per variant.
- **Low confidence**: A segment does not reach the 95% confidence threshold.
- **Too early**: The experiment has not run long enough yet. Segments can appear as it
  collects more orders.

A dimension is also hidden when its orders are too similar to split into separate
segments.
:::

## Related pages

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