This export type provides insight into logged-in users that are members of a selected segment(s).
As with all Qubit exports, you can specify the level of reporting detail to get a much greater understanding of reportables and focus on the details you are really interested in.
For this export type, you can select:
When applying the date range filter, we look at logged-in users whilst they were members of that segment. The data generated from their activities before they entered and after they left the segment is not considered.
In the following example, the data between when the user leaves and re-joins is not considered:
meta_recordDate, which is in the timezone configured for the property
trUser. If email and Id are emitted in view, events, such as
ecView, we can also get the data from this event
INFO: Duplicate session events typically account for less than 1% of all session events.
Unique Id that identifies a signed-in user in a segment
User email of the signed-in user in the segment
Total number of conversions carried out by the visitor across their lifetime
Lifetime Total Order Value (Conversions)
Sum of all conversion amounts for the user across their lifetime
Additional fields not included in the dimensions and metrics table above:
The Qubit context_id
The name of the segment that the signed-in user belongs to
As well as analyzing the metrics for visitors broken down by segment, you can use the data for targeting on other channels, such as CRM or email marketing.
To do this:
INFO: In your export, emails are stored in the
userEmail column and user Ids in the
When defining your schema, you must define one column as your primary key so we can join the data and the column must contain email addresses or user Ids. The column name is not important but the data types must match.
In the following example, we see the user has defined a schema and chosen to retain the naming used in the export
userEmail for the primary key. Note also the data type is Email Address:
In this next example, we see the user has defined a schema and chosen a custom name
user_id for the primary key. Note also the data type is Number:
WARNING: You must filter out data for users that have not given consent to contact them. If your CRM, marketing cloud, or Email Service Provider does not include this check, then you will need to do it manually.
TIP: You can of course perform further exports to keep the data in your third-party tool up-to-date.
For more information on how to track visitors landing from certain campaigns, tagged up with UTM parameters, please see Segment conditions.