Map Adobe Analytics data feed columns to Customer Journey Analytics

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This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A multi-value variable corresponding to Asset IDs (GUIDs) of a set of Adobe Experience Manager Assets. Increments Impression Events.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Identifies the source of the asset event. Used in Adobe Experience Manager.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Asset ID of an Adobe Experience Manager asset. Increments Click Events.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The AMO ID dimension, used in Adobe Advertising integrations.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The AMO EF ID dimension, used in Adobe Advertising integrations.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the browser.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

The Browser Height dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Browser Width

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Tracking Code dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Specifies the mobile carrier.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

You cannot collect both user agent information and device lookup information simultaneously; population of these dimensions are mutually exclusive. You must choose if you want to collect user agent directly or device lookup information (based on user agent) when Configuring a datastream.

The Site sections dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Client hints collected through the HTTP request header.

In Adobe Analytics, client hints were included as a concatenated string in this column. It is considered a more modern approach than the user_agent column.

You cannot collect both user agent information and device lookup information simultaneously; population of these dimensions are mutually exclusive. You must choose if you want to collect user agent directly or device lookup information (based on user agent) when Configuring a datastream.

Client hints collected through the User-Agent Client Hints JavaScript API.

In Adobe Analytics, client hints were included as a concatenated string in this column. It is considered a more modern approach than the user_agent column.

You can collect this data using the highEntropyUserAgentHints context string when configuring the Web SDK. Multiple XDM fields are populated instead of one long concatenated string:

• Operating system version: xdm.environment.browserDetails.userAgentClientHints.platformVersion
• Architecture: xdm.environment.browserDetails.userAgentClientHints.architecture
• Device model: xdm.environment.browserDetails.userAgentClientHints.model
• Bitness: xdm.environment.browserDetails.userAgentClientHints.bitness
• Browser vendor: xdm.environment.browserDetails.userAgentClientHints.vendor
• Browser name: xdm.environment.browserDetails.userAgentClientHints.brand
• Browser version: xdm.environment.browserDetails.userAgentClientHints.version

See User agent client hints for more information.

You cannot collect both user agent information and device lookup information simultaneously; population of these dimensions are mutually exclusive. You must choose if you want to collect user agent directly or device lookup information (based on user agent) when Configuring a datastream.

The Activity Map link dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

This column does not apply because Customer Journey Analytics does not yet support Activity Map.

The Activity Map link by region dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

This column does not apply because Customer Journey Analytics does not yet support Activity Map.

The Activity Map page dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

This column does not apply because Customer Journey Analytics does not yet support Activity Map.

The Activity Map region dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

This column does not apply because Customer Journey Analytics does not yet support Activity Map.

Color depth ID based on the value of the c_color column.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

Numeric ID representing the Connection type dimension.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

The Cookie support dimension.
Y: Enabled
N: Disabled
U: Unknown

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the country of the visitor. References the country.tsv lookup table.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

The currency code that was used during the transaction. Set using currencyCode.

xdm.commerce.order.currencyCode

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Determines if the hit is a mobile background hit.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

Customer Journey Analytics does not have a native concept of event type where it automatically includes or excludes hits based on the context of the hit. You can use xdm.eventType to help determine which events should be included and excluded in most reports.

Timestamp-enabled report suites only. The timestamp sent with the hit, based in UNIX® time.

Customer Journey Analytics does not have a concept of timestamp vs. non-timestamp report suites. Use xdm.timestamp instead, and adjust component settings as desired.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The custom visitor ID, if set using visitorID.

Customer Journey Analytics supports any number of identities using identityMap. If your organization uses custom identities, it is likely within the identity map.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Consent management opt-in dimension. Multiple values can be present per hit, separated by a pipe (\|). Valid values include DMP and SELL.

If your organization has a data management platform, it likely populates the desired XDM fields for this dimension.

The Consent management opt-out dimension. Multiple values can be present per hit, separated by a pipe (\|). Valid values include SSF, DMP, and SELL.

If your organization has a data management platform, it likely populates the desired XDM fields for this dimension.

The time of the hit in readable format, based on the report suite’s time zone.

You can use xdm.timestamp and apply the Date or Date-time Format component setting.

The Domain dimension. Based on the visitor’s Internet access point.

Enable Network lookup when Configuring a datastream. The XDM field is xdm.environment.domain if it is included in your schema.

Only used in report suites containing hit copy VISTA rules. Indicates which report suite that the hit was copied from.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

This column does not apply because Customer Journey Analytics does not have a concept of VISTA rules.

Lists each event that was counted as a duplicate.

This Analytics data feed column contains data that cannot be translated to a Customer Journey Analytics equivalent because of data architecture differences.

Customer Journey Analytics does not have a singular field that acts as a deduplicate flag for all metrics. Instead, each metric contains its own Metric deduplication component settings. As such, there is no equivalent field in Customer Journey Analytics for this Adobe Analytics data feed column.

A flag that determines if the purchase event for this hit is ignored because it is a duplicate.

While there isn’t a direct translation to this Analytics data feed column, its functionality of acting to deduplicate purchases still exists. If using the Commerce Details field group, you can set Metric deduplication component settings where the Deduplication ID is xdm.commerce.purchases.id.

If a direct translation is required where you want a flag for duplicate purchases, you can use a Derived field using the Deduplicate function in the ruleset.

The EF ID, used in Adobe Advertising integrations.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Custom variables 1-250. Used in eVar dimensions. Each organization uses eVars differently. The best place for more information on how your organization populates respective eVars would be a solution design document specific to your organization.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Comma-separated list of numeric IDs that represent events triggered on the hit. Includes both commerce events and custom events 1-1000. Uses event.tsv lookup.

This column likely maps to dozens of separate metrics, depending on your implementation. Adobe recommends the following process to map each respective metric in Customer Journey Analytics to its numeric value represented in this Analytics data feed column:

1. Use the event.tsv lookup to map each numeric value to its metric name.
2. Use your solution design document to map each Analytics event name to its corresponding metric name in Customer Journey Analytics.
3. Select the mapped component in the Data Views UI and note its component ID. If the component ID is too unwieldy, you can populate the data feed alias ID field and use that instead.
4. Repeat for every metric that your organization uses.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

If your schema uses the Commerce Details field group, some metrics might directly map to the following XDM fields:

• Checkouts: xdm.commerce.checkouts.value
• Cart adds: xdm.commerce.productListAdds.value
• Cart opens: xdm.commerce.productListOpens.value
• Cart removals: xdm.commerce.productListRemovals.value
• Cart views: xdm.commerce.productListViews.value
• Product views: xdm.commerce.productViews.value
• Orders: xdm.commerce.purchases.value

Some metrics might use event serialization, which is how Adobe Analytics allows full control over deduplication. You can use the Metric deduplication component setting to achieve deduplication parity.

• If your metric deduplicates by visit in Adobe Analytics, you can set the deduplication scope to session in that metric’s component settings.

• If your metric deduplicates by event ID in Adobe Analytics, it is likely that the XDM object for that metric contains both a value and id field. If your schema uses the Commerce Details field group, those metrics likely reside in these XDM fields, which you can set the Deduplication ID field in the metric’s component settings:

  • Checkouts: xdm.commerce.checkouts.id
  • Cart adds: xdm.commerce.productListAdds.id
  • Cart opens: xdm.commerce.productListOpens.id
  • Cart removals: xdm.commerce.productListRemovals.id
  • Cart views: xdm.commerce.productListViews.id
  • Product views: xdm.commerce.productViews.id

If you’re looking to deduplicate the Orders metric, see duplicate_purchase.

A flag that determines if the hit is excluded from reporting. The visit_num column is not incremented for excluded hits.

Customer Journey Analytics does not honor “excluded hits” out of the box. However, you can recreate this functionality if you have an XDM field that flags certain hits to be excluded:

1. Ensure that the XDM field that flags excluded hits is included as a component (dimension or metric, depending on how you have this flag set up). Selecting Hide component in reporting is likely beneficial for this field.
2. In Data view settings, select the Add segment drop-down menu and select Create segment.
3. Create a segment that excludes all events where your exclude hit component exists or contains values that you want to exclude.
4. Select Save on both the segment and the data view.

Excluded hits now do not exist in Customer Journey Analytics reporting, but are still available in data feed exports.

A numeric ID that represents the referrer type of the very first referrer of the visitor.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

A lookup ID of JavaScript version, based on j_jscript.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

The Java enabled dimension.
Y: Enabled
N: Disabled
U: Unknown

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the visitor’s language.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

List of Audience Manager segment IDs that the visitor belongs to. The post_mc_audiences column changes the delimiter to --**--.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile action. Automatically collected when trackAction is called in mobile implementations. Allows for automatic action pathing in the app.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile app ID. Stores the application name and version in the following format: [AppName] [BundleVersion]

xdm.application.name + xdm.application.version

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The name or ID of the content that displayed the link. Populated by Mobile App Acquisition.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Marketing medium, such as banner or email. Populated by Mobile App Acquisition.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The name of the campaign, also stored in the campaign variable. Populated by Mobile App Acquisition.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Original referrer, such as newsletter or social media network. Populated by Mobile App Acquisition.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Paid keywords or other terms you want to track with this acquisition. Populated by Mobile App Acquisition.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Number of the weekday that the app was launched on.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Number of days since the app was run for the first time.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Number of days since the app was last run.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile device name. On iOS, it is stored as a comma-separated 2-digit string. The first number represents the device generation, and the second number represents the device family.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Defines the hour of the day that the app was launched. Follows 24-hour numerical format.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile install date. Provides the date of the first time that a user opens the mobile app.

Since Customer Journey Analytics uses report-time attribution for every component, it does not have a concept of persistence beyond its lookback window. This Analytics data feed column references visitor-level behavior that extends to the visitor’s entire history. The longer the lookback window is for this component in Customer Journey Analytics, the closer it can match to Adobe Analytics functionality.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Increments by one each time the mobile app is launched.

Since Customer Journey Analytics uses report-time attribution for every component, it does not have a concept of persistence beyond its lookback window. This Analytics data feed column references visitor-level behavior that extends to the visitor’s entire history. The longer the lookback window is for this component in Customer Journey Analytics, the closer it can match to Adobe Analytics functionality.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Collected from the context data variable a.message.button.id. Used for in-app messaging to identify the button that closed the message.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

In-app Message ID

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

In-app Message Online

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Collected from the context data variable a.push.optin. Set to “true” when the user opts in to push messaging; otherwise the value is “false”.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Collected from the context data variable a.push.payloadid. Used in push messaging as the payload identifier.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile Services operating system version

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile Services Push opt-in

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile Services Push payload ID

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Resolution of the mobile device. [Width] x [Height] in pixels.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

If the user is using a mobile device, the numeric ID of the device.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

List variable values. Contains a delimited list of custom values depending on implementation. The post_mvvar1 - post_mvvar3 columns replace the original delimiter with --**--.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The list variable values that were set on the current hit. Replaces the original delimiter with --**--. The post columns typically do not contain data.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the operating system of the visitor. Based on the user_agent column.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

When configuring a datastream, you can enable Device lookup. If enabled, check the Operating system checkbox. Doing so automatically populates the following XDM fields if you have included these fields in your schema:

• OS vendor: xdm.environment.operatingSystemVendor
• OS name: xdm.environment.operatingSystem
• OS version: xdm.environment.operatingSystemVersion

You cannot collect both user agent information and device lookup information simultaneously; population of these dimensions are mutually exclusive. You must choose if you want to collect user agent directly or device lookup information (based on user agent) when Configuring a datastream.

The Page dimension. If the pagename variable is empty, Analytics uses page_url instead.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Similar to pagename, except it does not fall back to page_url. Only the post column is available.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The type of hit that is sent in the image request (standard hit, download link, custom link, exit link).

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

Only used in link tracking image requests. The URL of the download link, exit link, or custom link clicked.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Only used in link tracking image requests. The custom name (if specified) of the link. Sets the Custom link, Download link, or Exit link depending on the value in page_event.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Pages not found dimension, which is typically used for 404 pages.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

page_url: The URL of the hit. Uses a data type of text.
post_page_url: Stripped for link tracking image requests (tl()).

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used in the Persistent cookie support dimension. Indicates if the visitor supports cookies that are not discarded after each hit.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile Services point of interest name

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Mobile Services distance to point of interest center

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The products page variable. Helps populate several dimensions and metrics, including Category, Product, Units, and Revenue.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Custom traffic variables 1-75. Used in Prop dimensions.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Unique identifier for a purchase, as set using the purchaseID variable. Used by the duplicate_purchase column.

xdm.commerce.order.purchaseID

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Referrer dimension. Note that while referrer uses a data type of varchar(255), post_referrer uses a data type of varchar(244).

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the resolution of the monitor. Used in the Monitor resolution dimension.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

A numeric ID that represents the search engine that referred the visitor to your site. Used in Search Engine dimensions.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

Keyword ID used in Adobe Advertising integrations.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used in Adobe Target integrations. Represents all tests currently qualified for. Format is: TargetCampaignID:TargetRecipeID:TargetType\|Event/Action.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used in Adobe Target integrations. Represents all tests the hit qualified for.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A unique identifier where various data points can be uploaded later through data sources. Collected using the transactionID variable.

xdm.commerce.order.payments[0].transactionID

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Local time for the visitor. Format is: M/D/YYYY HH:MM:SS Month (0-11, 0=January) Timezone offset (in minutes)

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used in the Server dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that identifies the Last touch channel dimension.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

A numeric ID that identifies the First touch channel dimension.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

The Content streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad in pod position streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad length (variable) streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad name (variable) streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad player name streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Ad pod streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Advertiser streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Campaign ID streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content channel streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Chapter streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content type streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Day part streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Episode streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Media feed type streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Genre streaming media services dimension. This dimension allows multiple values in the same hit, delimited by a comma.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content length (variable) streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The MVPD streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content name (variable) streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Network streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Media path streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content player name streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Average bitrate streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Bitrate changes streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Buffer events streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Total buffer duration streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Dropped frames streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Player SDK error IDs streaming media services dimension. This dimension allows multiple values in the same hit.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Time to start streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Season streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Content segment streaming media services imension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Media session ID streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Show streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Show type streaming media services dimension.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used with visid_low to uniquely identify a visitor.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Used with visid_high to uniquely identify a visitor.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

Not for external use; internally used by Adobe for processing optimizations. A numeric ID that represents the method used to identify the visitor.
0: Custom visitor ID or Unknown/not applicable
1: IP and user agent fallback
2: HTTP Mobile Subscriber Header
3: Legacy cookie value (s_vi)
4: Fallback cookie value (s_fid)
5: Identity Service

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

The Search keyword dimension. This column uses a non-standard character limit of varchar(244) to accommodate back-end logic used by Adobe. The post-processed column is **post_keywords**, not **post_visit_keywords**.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.

A numeric ID that represents the referrer type of the first referrer of the visit.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

A numeric ID that represents the first search engine of the visit.

This Analytics data feed column uses a lookup table to identify the desired value. In Customer Journey Analytics, the value is provided directly without any lookup tables. Ensure that your workflow accommodates the final value instead of an intermediate lookup value.

Helps populate the Zip code dimension. See also geo_zip.

This Analytics data feed column contains both a pre-processed version and a post-processed version (a prefix of post_). Columns with a prefix of post_ contain the value that is ultimately used in reporting. Most organizations solely use post_ columns when they are available. The following table compares the properties of these columns:

Since Customer Journey Analytics does not have a concept of pre-processing and post-processing, recreating both columns in CJA data feeds is difficult. If you would like approximations of these columns, you can drag the same XDM field multiple times into the dimensions column to create multiple components with different attribution settings:

• Pre-processed column: No attribution
• Post-processed column: Apply the same allocation and expiration settings as its Analytics variable in data view settings. Most components would use an allocation of “Last” and an expiration of “Visit”.