Frequently asked questions
You can use a Flow visualization with the Mobile Device Type dimension.
- Log in to Adobe Analytics and create a new blank Workspace project.
- Click the Visualizations tab on the left, and drag a Flow visualization to the canvas on the right.
- Click the Components tab on the left, and drag the dimension ‘Mobile Device Type’ to the center location labled ‘Dimension or Item’.
- This flow report is interactive. Click any of the values to expand the flows to subsequent or previous pages. Use the right-click menu to expand or collapse columns. Different dimensions can also be used within the same flow report.
CDA’s cross-device stitching occurs in two concurrent processes.
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The first process is called “live stitching”, which occurs as the data streams into Adobe Analytics. During live stitching CDA does the best it can to restate the data at a person level. However, if the person is unknown at the time of live stitching then CDA falls back to the visitor ID to represent the person.
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The second process is called “replay.” During replay, CDA goes backwards in time and restates historical data, where possible, within a specified lookback window. This lookback window is either 1 day or 7 days, depending on how you requested CDA to be configured. During replay, CDA attempts to restate hits where the person was previously unknown.
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If using a device graph, Adobe keeps Device Graph mappings for approximately 6 months. An ECID that has no activity for more than six months is removed from the graph. Data already stitched in CDA is not affected; subsequent hits for that ECID are treated as a new person.
Using a custom visitor ID is a legacy method to connect users across devices. With a custom visitor ID, you use the visitorID
variable to explicitly set the ID that is used for visitor logic. The visitorID
variable overrides any cookie-based IDs that are present.
Custom visitor IDs have several undesirable side effects that CDA overcomes or minimizes. For example, the custom visitor ID methodology has no replay capabilities. If a user authenticates in the middle of a visit, the first part of the visit associates with a different visitor ID than the latter part of the visit. The separate visitor IDs results in visit and visitor inflation. CDA restates historical data so unaunthenticated hits belong to the correct person.
visitorID
variable is still used in the source report suite. However, CDA ignores the visitorID
variable in the virtual report suite if a user authenticates.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.
- If using a device graph, the ability to handle shared devices is limited. The device graph uses an algorithm to determine ownership of a “cluster”, and can change each time that cluster is published. Users of the shared device are subject to which cluster they belong to.
- If using field-based stitching, the prop or eVar that you choose to help identify logged in users overrides other identifiers. Shared devices are considered separate people, even if they originate from the same device.
In some situations, an individual user can associate with a large number of ECIDs. This can occur if the individual uses a lot of browsers or apps, and can be exacerbated if they frequently clear cookies or use the browser’s private or incognito browsing mode.
- If using a device graph, CDA caps the number of ECIDs that ties to a given user ID to 50. If a user ID associates with too many ECIDs, the device graph assumes that the user ID is invalid and removes the cluster associated with that user ID. The user ID is then added to a blocklist to prevent it from being added to any clusters in the future. The result in reporting is that user ID is not stitched across devices.
- If using field-based stitching, the number of devices is irrelevant in favor of the prop/eVar you choose to help identify logged in users. A single user can belong to any number of devices without impacting CDA’s ability to stitch across devices.
These two metrics are roughly equivalent to each other. Differences between the 2 metrics occur when:
- A shared device maps to multiple people. In this scenario, 1 unique visitor is counted, while multiple unique devices are counted.
- A device has both non-stitched and stitched traffic from the same visitor. For example, a browser generated identified stitched traffic + historical anonymous traffic that was not stitched. In this case, 1 unique visitor is counted, while 2 unique devices are counted.
See Unique Devices for more examples and details around how it works.
Yes. Analysis Workspace uses the 2.0 API to request data from Adobe’s servers, and you can view API calls Adobe uses to make your own reports:
- While logged in to Analysis Workspace, go to Help > Enable debugger.
- Click the debug icon in the desired panel, then select the desired visualization and time of the request.
- Locate the JSON request, which you can use in your API call to Adobe.
- If using a device graph, a custom ID based on their cluster is the primary identifier.
- If using field-based stitching, a custom ID based on the prop/eVar you choose is the primary identifier.
Both of these identifiers are calculated by Adobe at the time the report is run, also known as Report-time processing. The nature of Report-time processing means that it is not compatible with Data Warehouse, data feeds, or other export features that Adobe offers.
The advantage of the 7-day replay lookback window is that CDA is able to go back further in time to try to associate previously anonymous events with some person who later logged in within those 7 days. The disadvantages of the 7-day lookback window are 1) replay only runs once per week, and 2) the most recent 7 days are subject to change.
The advantages of using the 1-day replay lookback window are 1) replay runs every day and 2) only yesterday is subject to change. The disadvantage of the 1-day lookback window is that CDA is only able to go back 1 day to try to associate previously anonymous events with a person who logged in yesterday.
The number of the ‘Identified People’ metric can be slightly higher if the identifier prop/eVar value runs into a hash collision.
For Field-based stitching, the identifier custom variable is case-sensitive. The number of the ‘Identified People’ metric can be significantly higher if identifier values do not match case. For example, if bob
and Bob
are sent and expected to be the same person, CDA interprets these two values as distinct.