Identity stitching (or simply, stitching) is a powerful feature that elevates an event dataset’s suitability for cross-channel analysis. Cross-channel analysis is a main use case that Customer Journey Analytics can handle, allowing you to seamlessly combine and run reports on multiple datasets from different channels, based on a common identifier (person ID).
When you combine datasets with similar person IDs, attribution is carried over across devices and channels. For example, a user first visits your site through an advertisement on their desktop computer. That user encounters an issue with their order, then gives your customer service team a call to help resolve it. With cross-channel analysis, you can attribute call center events to the ad that they originally clicked.
Unfortunately, not all event-based datasets that are part of your connection in Customer Journey Analytics are sufficiently populated with data to support this attribution out of the box. Especially, web-based or mobile-based experience datasets often don’t have an actual person ID information available on all events.
Stitching allows rekeying identities within one dataset’s rows, making sure the person ID (stitched ID) is available on each event. Stitching looks at user data from both authenticated and unauthenticated sessions to determine the common transient ID value that can be used as stitched ID. This rekeying allows for resolving disparate records to a single stitched ID for analysis at the person level, rather than at the device or cookie level.
You benefit from cross-channel analysis if you combine one or more of your stitched datasets with other datasets, such as call center data, as part of defining your Customer Journey Analytics connection. This assumes that those other datasets already contain a person ID on every row, similar to the stitched ID.
You must have the Select package or higher in order to use the functionality described in this section. Contact your administrator if you’re unsure which Customer Journey Analytics package you have.
Failure to meet all prerequisites can result in the inability to properly conduct cross-channel analysis.
Before using stitching, make sure that your organization is prepared with the following:
Import the desired data into Adobe Experience Platform:
The event dataset in Adobe Experience Platform to which you want to apply stitching must have two columns that help identify visitors:
Both columns (persistent ID and transient ID) must be defined as an identity field with an identity namespace in the schema underlying the dataset you want to stitch. When using identity stitching in Real-time Customer Data Platform using the identityMap field group, you still need to add identity fields with an identity namespace, as Customer Journey Analytics stitching discussed in this section does not support the identityMap field group. When adding an identity field in the schema while also using the identityMap field group, do not set the additional identity field as a primary identity, as this will interfere with the identityMap field group used for the Real-time Customer Data Platform.
Stitching includes merging authenticated and unauthenticated user data. Ensure that you comply with applicable laws and regulations, including obtaining necessary end-user permissions, before activating stitching on an event dataset. See Define identity fields in the UI for more information.
Once your organization meets all prerequisites and understands the limitations, you can follow these steps to start using stitching in Customer Journey Analytics:
Contact Adobe Customer Support with the following information:
The Adobe Customer Support works with Adobe engineering to enable stitching upon receiving your request. Once enabled, a new rekeyed dataset that contains a new Stitched ID column appears in Adobe Experience Platform. Adobe Customer Support can provide the new dataset’s ID.
When first turned on, Adobe provides a backfill of stitched data that goes back 60 days.
If you want to use the new stitched dataset in a cross-channel analysis, you need to add it to a connection in Customer Journey Analytics together with any other needed datasets. Choose the correct person ID for each dataset.
Create a data view based on the connection.
Once the data view is set up, you can run your Customer Journey Analytics reporting analysis across channels and devices.
Apply any change that you make to the global event dataset schema also to the new stitched dataset schema, otherwise it breaks the stitched dataset.
If you remove the source dataset, the stitched dataset stops processing and gets removed by the system.
Data usage labels are not automatically propagated to the stitched dataset schema. If you have data usage labels applied to the source dataset schema, you need to manually apply these data usage labels to the stitched dataset schema. See Managing data usage labels in Experience Platform for more information.
Stitching is a groundbreaking and robust feature, but has limitations on how it can be used.
Do not confuse stitching with:
The merge of two or more datasets. Stitching applies to one dataset only. Merging of datasets occurs as a result of setting up a Customer Journey Analytics connection and selecting the same Person ID across the selected datasets in the connection.
The join of two datasets. In Customer Journey Analytics, a join is often used for lookups or classifications in Analysis Workspace. Although stitching uses join functionality, the process itself involves more than joins.