Segment-to-Trait Overlap Report
Returns data on the number of unique users shared between a particular trait and an entire segment.
Overview
As an optimization tool, the Segment to Trait Overlap reports helps you build highly focused segments or expand segment reach. For example, you can create focused segments and traits with high overlap to reach a particular audience. However, a lot of overlap may mean fewer unique users (less reach). Running this report to help expand reach by removing traits with a lot of segment overlap and replacing them with traits that have less overlap.
Sample Report
The following illustration provides a high-level overview of the Segment-to-Trait Overlap report.
Drill Down on Individual Data Points
Select an individual point to view data details in a pop up window. Your click actions automatically update data displayed in the report.
Comparing Segments to Traits
Describes how you can compare segments and traits to derive meaningful information from the results.
Comparing Trait and Segment Uniques: An Example
At first glance, it may seem illogical to compare segments to traits and attempt to draw conclusions from the results. After all, segments and traits are different, so how can data derived from disparate items have meaning? However, in this case, we’re not comparing traits and segments, but the number of unique visitors shared between them. The shared unique visitor count provides the common value that makes a segment to trait comparison possible.
The following diagram illustrates the relationship between a trait and the segment it belongs to. In this case, we have a trait with 10 visitors and a segment with 1,000 visitors. They share 3 unique visitors in common.
The unique visitor count is the common, constant value shared between these different classes of objects. As a result, you can determine the unique visitor relationship between them as follows:
- The trait shares 30% of its unique visitors with the segment (3/10 = 0.30).
- The segment shares 0.3% of its unique visitors with the trait (3/1,000 = 0.003)
Find Value in Segment to Trait Comparisons
Looking at the overlap between traits and segments can help you estimate the total available visitor pool (forecasting) or find inefficient segments with too much overlap.
To determine the available visitor pool, sum the difference between the trait total (less overlap) and the segment total (less overlap).
This segment-trait combination could reach up to 1004 new users.
Understanding the Data Filters in the Segment-to-Trait Overlap Report:anchor-data-filters-s2t-report:
Describes how the trait and segment unique overlap % sliders work.
The Segment-to-Trait overlap report lets you use two sliders to filter data by the overlap % by trait or segment.
- Filter Trait Uniques %: Filters data by the % of unique visitors shared between the trait and the segment.
- Filter Segment Uniques Overlap %: Filters data by the % of unique visitors share between the segment and the trait.
Example
The following diagram illustrates the difference between the trait uniques % and the segment uniques %. In this case, the trait and segment share 3 unique visitors. As proportions:
- The trait shares 30% of its unique visitors with the segment (3/10 = 0.30).
- The segment shares 0.3% of its unique visitors with the trait (3/1,000 = 0.003)
Segment-to-Trait Data Pop Fields Defined
Describes the metrics displayed in the popup window when you click an individual data point.
The popup for the Segment-to-Trait Overlap report contains the metrics below. Note that the uniques metric in the table represents your real-time users.
Defines the type of provider a trait belongs to. Can be either:
- First-party (your own trait).
- Third-party (from an outside data partner/vendor).