Here are some frequently asked questions around stitching:
You can use a Flow visualization with the Dataset ID dimension.
If you would like to rename dataset ID dimension items, you can use a lookup dataset.
The lookback window for rekeying depends on your desired frequency of data replay. For example, if you set up stitching to replay data once every week, the lookback window for rekeying is seven days. If you set up stitching to replay data every day, the lookback window for rekeying is one day.
In some situations, it is possible that multiple people log in from the same device. Examples include a shared device at home, shared PCs in a library, or a kiosk in a retail outlet.
The transient ID overrides the persistent ID, so shared devices are considered separate people (even if they originate from the same device).
In some situations, an individual user can associate with many persistent IDs. An example is an individual frequently clearing browser’s cookies or using the browser’s private/incognito mode.
The number of persistent IDs is irrelevant in favor of the transient ID. A single user can belong to any number of devices without impacting Customer Journey Analytics’s ability to stitch across devices.
Live stitching is available approximately one week after Adobe enables stitching. Backfill availability depends on the amount of existing data. Small datasets (less than 1 million events per day) typically take a couple days, while large data sets (1 billion events per day) can take a week or more.
Cross-device analytics is a feature specific to traditional Adobe Analytics that allows you to understand how people operate across devices. It offers two workflows to link device data together: field-based stitching and the device graph.
Cross-channel analysis is a use case specific to Customer Journey Analytics that allows you to understand how people operate across both devices and channels. It stitches a dataset’s person ID, allowing that dataset to be seamlessly combined with other datasets. This feature operates in design similarly to cross-device analytics field-based stitching, but the implementation is different due to differing data architecture between traditional Analytics and Customer Journey Analytics. See Stitching and the cross-channel analysis use case for more information.
Adobe handles GDPR and CCPA requests in accordance with local and international laws. Adobe offers the Adobe Experience Platform Privacy Service to submit data access and deletion requests. The requests apply to both the original and rekeyed datasets.
If the Persistent ID field is blank on an event in a dataset being stitched , the Stitched ID for that event in determined in one of two ways:
Be cautious of ‘person collapse’, which occurs when stitching is applied to data that uses placeholder values for Transient IDs. In the example table below, undefined person IDs originating from a dataset sourced from a CRM system are populated with the value ‘Undefined’ resulting in incorrect representation of persons.
|Event||Timestamp||Persistent ID (Cookie ID)||Transient ID (Login ID)||Stitched ID (after replay)|
|4 devices||2 people:
Events 1, 4, 7, 9, 10 dropped
Cory, Unauthenticated (collapsed to one person)
Certain metrics in Customer Journey Analytics are similar to metrics in traditional Analytics, but others are different, depending on what you are comparing. The table below compares several common metrics:
|Customer Journey Analytics stitched data||Customer Journey Analytics unstitched data||Adobe Analytics||Analytics Ultimate with CDA|
|People = Count of distinct Person IDs where Stitched ID is chosen as Person ID. People may be higher or lower than Unique Visitors in traditional Adobe Analytics, depending on the outcome of the stitching process.||People = Count of distinct Person IDs based on the column selected as Person ID. People in Analytics source connector datasets is similar to Unique Visitors in traditional Adobe Analytics if
||Unique Visitors = Count of distinct visitor IDs. Unique Visitors may not be the same as the count of distinct ECIDs.||See People.|
|Sessions: Defined based on the session settings in the Customer Journey Analytics data view. The stitching process may combine individual sessions from multiple devices into a single session.||Sessions: Defined based on the session settings specified in the Customer Journey Analytics data view.||Visits: See Visits.||Visits: Defined based on the session settings specified in the CDA virtual report suite.|
|Events = count of rows in the stitched data in Customer Journey Analytics. This metric is typically close to Occurrences in traditional Adobe Analytics. Note, however, the FAQ above regarding rows with a blank Persistent ID.||Events = count of rows in the unstitched data in Customer Journey Analytics. This metric is typically close to Occurrences in traditional Adobe Analytics. Note, however, that if any events have a blank Person ID in the unstitched data in Experience Platform data lake, these events are not included in Customer Journey Analytics.||Occurrences: See Occurrences.||Occurrences: See Occurrences.|
Other metrics can be similar in Customer Journey Analytics and Adobe Analytics. For example, the total count for Adobe Analytics custom events 1-100 is comparable between traditional Adobe Analytics and Customer Journey Analytics (whether stitched or unstitched). Differences in capabilities) such as event de-duplication between Customer Journey Analytics vs. Adobe Analytics can cause discrepancy between the two products.
No, Customer Journey Analytics cannot currently use Identity Map fields for stitching.