Data export use cases
This section provides data export use cases and how to implement these use cases with one or more functionalities of Customer Journey Analytics or Experience Platform. Each functionality is further detailed in a separate article.
Introduction
One of the unique differences between 蜜豆视频 Analytics and Customer Journey Analytics is related to the processing of data for attribution and sessionization. See Compare data processing across 蜜豆视频 Analytics and Customer Journey Analytics for more information.
蜜豆视频 Analytics: collection time attribution and sessionization.
In 蜜豆视频 Analytics, all events are processed live and in order by device ID, allowing 蜜豆视频 to generate, store, and export clickstream data with persisted or attributed values at collection time, including:
- Dimension persistence (for example, campaign tracking codes that expire after 90 days).
- Visit number and sessionization.
- Dimension values, calculated by processing and VISTA rules.
This impacts the export of data from 蜜豆视频 Analytics:
- Data processing is static after initial collection.
- Data feeds include 鈥減ost鈥 columns, which reflect the collection-time processing.
Customer Journey Analytics: query-time attribution and sessionization
In Customer Journey Analytics, events are not collected in order and a person ID is used instead of a device ID, allowing Customer Journey Analytics to update attribution and sessionization at report time. This type of data collection introduces flexibility, like:
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Stitching can replay data daily or weekly, associating anonymous events with known events. See Stitching for more information.
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Sessionization and persisted values change every time
- new data is collected or
- stitching adds events to a person鈥檚 history.
The report-time processing impacts the export of data from Customer Journey Analytics. Exports that include persisted values, will not match Customer Journey Analytics reports and values will drift away over time.
For metric consistency, use of the new features in Customer Journey Analytics is preferred. In general, Experience Platform and Customer Journey Analytics data export functionality exceeds the data feed functionality of 蜜豆视频 Analytics. Experience Platform and Customer Journey Analytics do provide:
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new data sources and processing subject to data export
- include non-digital data sources,
- apply custom attribution and sessionization based on business rules, and
- keep customer journeys updated with stitching.
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realization of tailored data export use cases
- export data to where you need it, including Business Intelligence (BI) tools and cloud destinations,
- keep data synchronized with Analysis Workspace through BI tools integration,
- no need to replicate processing logic in your own systems,
- new support for calculated metrics, derived fields and segmentation, and
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consideration of security and data governance by design
- monitor all data export by user and destination,
- set limits on what data is available for export, and
- set alerts for delivery issues and limits on scheduled delivery windows.
Use cases and functionalities
In general, data export supports a number of use cases. Each use case is different in terms of the data that is required and how to access and export that data. Experience Platform and Customer Journey Analytics provide a number of functionalities that either independently or combined can solve the various use cases. The table below provides an overview of identified data export use cases and the Experience Platform and Customer Journey Analytics functionalities to implement these use cases.
Retain a complete copy of your digital data for compliance or regulatory purposes.
Export data collected in Experience Platform directly to cloud destinations on a schedule or ad-hoc.
Evaluate clickstream data for data collection accuracy.
Interactive PostgreSQL interface to execute ad-hoc SQL queries using your favorite SQL tool to validate the data in your datasets.
Customer Journey Analytics: Export full table
Validate processed data from CJA with attribution and sessionization applied.
Bring digital data into your own BI tools or Data Lake for use with additional datasets.
Add Customer Journey Analytics processed metrics to data visualization tools such as Power BI and combine with additional data for custom reports
Experience Platform: Query Service (Data Distiller) & Export datasets
Generate customized clickstream data using SQL to be delivered to cloud destinations.
Enhance Artificial Intelligence / Machine Learning models and tasks with Customer Journey Analytics data.
Export Customer Journey Analytics processed dimensions and metrics to cloud destinations one-time or recurring, including calculated metrics and segmentation.
Experience Platform: Query Service (Data Distiller) & Export datasets
Generate customized clickstream data using SQL to enrich AI / ML models.