The Adobe Target-to-Adobe Analytics integration, known as Analytics for Target (A4T), supports Auto-Allocate and Auto-Target activities.
The A4T integration lets you:
Ensure that you have implemented A4T for use with A/B Test and Experience Targeting activities. If you use analyticsLogging = client_side
, you must also pass the sessionId
value to Analytics. For more information, see Analytics for Target (A4T) reporting in the Adobe Target Developer Guide.
To get started:
While creating an A/B Test activity, on the Targeting page, select one of the following options as the Traffic Allocation Method:
For more information and step-by-step instructions, see Create an Auto-Allocate activity and Create an Auto-Target activity.
Select Adobe Analytics for your Reporting Source on the Goals & Settings page and select the report suite corresponding to your desired optimization goal.
Choose a Primary Goal metric.
See Supported goal metrics below for more information.
Save and activate your activity.
Auto-Allocate uses your selected metric to optimize the activity, driving visitors to the experience that maximizes your goal metric.
Or
Auto-Target uses your selected metric to optimize the activity, driving visitors to a personalized best experience.
Use the Reports tab to view your activity’s reporting by your choice of Adobe Analytics metrics. Click View in Analytics to dive deep and further segment your reporting data.
A4T for Auto-Allocate and Auto-Target lets you choose any of the following metric types as your primary goal metric for optimization:
After selecting Use an Analytics Metric, select Maximize Unique Visitor Conversion Rate to view available Adobe Analytics conversion metrics, and Maximize Metric Value per Visitor to explore Adobe Analytics custom events.
Target lets you choose metrics based on binomial events or metrics based on continuous events when using A4T for Auto-Allocate and Auto-Target activities.
Metrics based on binomial events: A binomial event either does or does not happen. Binomial events include a click, a conversion, an order, and so forth. These types of events are also sometimes referred to as Bernoulli, binary, or discrete events.
Metrics based on continuous events. Continuous metrics include revenue, number of products ordered, session duration, number of page views in session, and so forth. These types of events are also sometimes referred to as non-binomial or non-Bernoulli metrics.
As of the Adobe Target Standard/Premium 22.15.1 release (March 8 & 9, 2023), Target continues to support existing activities with the metrics that are now unsupported (listed in the following tables). However, after September 9, 2023, these metrics will no longer be supported in existing activities and all activities using non-supported metrics will be discontinued to force existing activity migration to the new behavior.
Metric name | No longer supported in: |
---|---|
averagepagedepth | Conversion Rate, Maximize Metric Value |
averagetimespentonsite | Conversion Rate, Maximize Metric Value |
bouncerate | Conversion Rate, Maximize Metric Value |
bounces | Conversion Rate, Maximize Metric Value |
entries | Conversion Rate, Maximize Metric Value |
exits | Conversion Rate, Maximize Metric Value |
pageviews | Maximize Metric Value |
reloads | Maximize Metric Value |
visitors | Conversion Rate, Maximize Metric Value |
visits | Maximize Metric Value |
Metric name | No longer supported in: |
---|---|
cartremovals | Maximize Metric Value |
pageviews | Maximize Metric Value |
visitors | Conversion Rate, Maximize Metric Value |
visits | Maximize Metric Value |
Some limitations and notes apply to both Auto-Allocate and Auto-Target activities. Other limitations and notes apply to one activity type or the other.
Auto-Target models continue to train every 24 hours, as usual. However, conversion event data coming from Analytics is delayed by an extra six to 24 hours. This delay means the distribution of traffic by Target trails the latest events recorded in Analytics. This delay has the largest effect in the first 48 hours after an activity is initially activated. The activity’s performance more closely mirrors Analytics conversion behavior after five days have elapsed.
Consider using Auto-Allocate instead of Auto-Target for short-duration activities in which most traffic occurs within the first five days of the activity’s life.
When using Analytics as the data source for an Auto-Target activity, sessions end after six hours have elapsed. Conversions occurring after six hours are not counted.
For more information, see Attribution models and lookback windows in the Analytics Tools Guide.
Although rich analysis capabilities are available in Adobe Analytics Analysis Workspace, a few modifications to the default Analytics for Target panel are required to correctly interpret Auto-Allocate and Auto-Target activities. These modifications are required due to differences between experimentation activities (manual A/B and Auto-Allocate) and personalization activities (Auto-Target).
This tutorial walks you through the recommended modifications for analyzing Auto-Allocate activities in Analysis Workspace.
For more information, see How to set up A4T reports in Analysis Workspace for Auto-Allocate activities in Adobe Target Tutorials.
This tutorial walks you through the recommended modifications for analyzing Auto-Target activities in Analysis Workspace.
For more information, see How to set up A4T reports in Analysis Workspace for Auto-Target activities in Adobe Target Tutorials.