Data views use cases

Last update: April 22, 2025

CREATED FOR:

  • User

These use cases illustrate the flexibility and power of data views in Customer Journey Analytics.

Use binding dimensions metrics

See the Use binding dimensions metrics use case for more details.

Use summary data

See the Use summary data use case for more details.

BI extension use cases

See the BI extension use cases on how to accomplish a number of use cases using the Customer Journey Analytics BI extension.

Create a metric from a string schema field

For example, when creating a data view, you could create an Orders metric from a Page Title schema field that is a string.

  1. On the Components tab, drag the Page Title into the Metrics section under Included components.

  2. Highlight the metric you just dragged in and rename it to Orders in the Component Settings on

  3. Open the Include/Exclude Values section and specify the following:

    1. Enable Set include exclude values.
    2. Select If all criteria are met from Match.
    3. Specify confirmation. This text for the page_title indicates that this page is related to placing an order. After reviewing all the page titles where those criteria are met, a 1 will be counted for each instance. The result is a new metric (not a calculated metric.) A metric that has included/excluded values can be used everywhere any other metric can be used. It works with Attribution IQ, segments, and everywhere else you can use standard metrics.

    Dimension to metric

  4. You can further specify an attribution model for this metric, such as Last Touch, with a Lookback window of Session.
    You can also create another Orders metric from the same field and specify a different attribution model. Such as First Touch, and a different Lookback window, such as 30 days.

Another example would be to use the Person ID, a dimension, as a metric to determine how many Person IDs your company has.

Use integers as dimensions

Previously, integers would automatically be treated as metrics in Customer Journey Analytics. Now, numerics (including custom events from Adobe Analytics) can be treated as dimensions. Here is an example:

  1. Drag the Duration integer into the Dimensions section under Included Components:

  2. You can now add Value Bucketing to present this dimension in a bucketed fashion in reporting. Without bucketing, each instance of this dimension would appear as a line item in Workspace reporting.

    Integer to dimension

Use numeric dimensions as metrics in flow diagrams

You can use a numeric dimension to get metrics into your Flow visualization.

  1. On the Data Views Components tab, drag the Marketing Channels schema field into the Metrics area under Included components.
  2. In Workspace reporting, this flow shows Marketing Channels flowing into Orders:

Marketing Channel flow from emails to Exit/orders.

Do sub-event filtering

This capability is specifically applicable to array-based fields. The include/exclude functionality lets you filter at the sub-event level, whereas segments built in the Segment builder only give you segmentation at the event level. You can do sub-event filtering by using include/exclude in Data views, and then reference that new metric/dimension in a segment at the event level.

For example, use the include/exclude functionality in Data views to focus only on products that generated sales of more than $50. So, if you have an order that includes a $50 product purchase and a $25 product purchase, the include/exclude functionality removes the $25 product purchase, not the entire order.

  1. On the Data Views Components tab, drag the Revenue schema field into the Metrics area under Included components.
  2. Select the metric and configure the following on the right side:
    a. Under Format, select Currency.
    b. Under Currency, select USD.
    c. Under Include/Exclude Values, select the checkbox next to Set include/exclude values.
    d. Under Match, select If all criteria are met.
    e. Under Criteria, select is greater than or equal.
    f. Specify 50 as the value.

These new settings allow you to view only high-value revenue and filter out anything below $50.

Use the No value options setting

Your company may have spent time training your users to expect “Unspecified” for dimensions in reports. The default for dimensions in Data views is “No value”. However, you can specify per dimension how No value should be reported. See the No value options for a dimension component.

No value options

Create multiple metrics with different attribution settings

Using the Duplicate feature at the top right, to create a number of Total Revenue metrics with different attribution settings like First Touch, Last Touch, and Algorithmic.

Don’t forget to rename each metric to reflect the differences, such as Total Revenue (Algorithmic)

Duplicate metric for different attribution settings

For more information on other data views settings, see Create data views.
For a conceptual overview of data views, see Data views overview.

New session and return session reporting

You can determine whether a session is indeed the first-ever session for a user or a return session. Based on the reporting window that you defined for this data view and a 13-month lookback window. This reporting lets you determine, for example:

  • What percentage of your orders are coming from new or return sessions?

  • For a given marketing channel, or a specific campaign, are you targeting first-time users or return users? How does this choice influence conversion rates?

One dimension and two metrics facilitates this reporting:

  • Session type - This dimension has two values: New and Returning. The New line item includes all the behavior (that is, metrics against this dimension) from a session that has been determined to be a person’s defined first session. Everything else is included in the Returning line item (assuming everything belongs to a session). Where metrics are not part of any session, they fall into the ‘Not applicable’ bucket for this dimension.

  • First-time Sessions. The First-time Sessions metric is defined as a person’s defined first session within the reporting window.

  • Return Sessions The Return Sessions metric is the number of sessions that were not a person’s first-time session.–>

To access the components:

  1. Go into the data view editor.
  2. Select the Components tab and then select Standard components from the left rail.
  3. Drag the Session type, First-time Sessions, and Return Sessions components into your data view.

New sessions are reported accurately almost always. The only exceptions are:

  • When a first session occurred before the 13-month lookback window.
    This session is ignored.

  • When a session spans both the lookback window and the reporting window.
    For example, you run a report from June 1 to June 15, 2022. The lookback window would span from May 1, 2021 to May 31, 2022. If a session starts on May 30, 2022 and ends on June 1, 2022, the session is included in the lookback window. And all sessions in the reporting window are counted as return sessions.