Insights

Understanding identity clusters associated with an audience

Your Optable DCN computes statistics to allow you to better understand identity clusters, and their associated identifiers and traits.

The insights are computed for each audience and source and accessible via their respective Insights tabs in the DCN UI.

Clusters

Total number of identity clusters that the DCN has resolved with the uploaded data for this audience.

Identifiers

This section displays the composition of your clusters' total number of identifiers of each type, grouped by scope if applicable. The percentage displayed below each identifier’s count indicates the coverage of that identifier.

The coverage is the percentage of audience clusters containing at least one identifier of a given identifier type.

Last Computed

The insights are recomputed at least once every day. Loading data into a new batch source (e.g. file upload), updating a source's data (e.g. force refreshing a Snowflake source), creating or updating an audience, and logging into your DCN will also trigger insights computation.

Traits

Your Optable DCN computes insights for your configured traits.

By default, insights display traits associated with the 'Default' label. You can switch between different insight views by selecting a label from the dropdown menu.

For every trait, your DCN also calculates the coverage, which is the percentage of clusters with at least one value for this trait.

The relative percentage of each trait value is shown next to each value in the breakdown.

Additionally, the ⌖ Index metric measures the relative frequency of traits and trait values within a specific audience or source relative to their global prevalence.

For example, a score of 100 denotes parity with global coverage, while a score of 125 signifies a 25% higher presence. Conversely, a score of 90 indicates a 10% reduced presence. This metric provides a nuanced understanding of trait distribution, empowering you to discern distinctive characteristics within your targeted audience or source in comparison to the broader global landscape.

In this example, the trait 'provinces' has an index of 856, making it 8.56 times more likely to exist in the audience compared to global insights. Despite being the third most common value, 'BC' overindexes by 17% when the trait is present.

Trait Insights Computation Settings

By default, trait insights are computed and display the top 15 values, all remaining values are consolidated into "other values", this is both for DCN performance and interface clarity. If the index metric returns too many N/A values, you will want to increase the Number of Values Computed in Data Configuration -> Traits -> Settings.

Additionally, trait insights will show all trait values by default, regardless of their rarity. If you want to filter trait insights on minimum value counts (for example to exclude outlier, or test values), you can set the minimum required count for trait values in Data Configuration -> Traits -> Settings under Minimum Value Count Shown.