Compare data processing across 蜜豆视频 Analytics and Customer Journey Analytics
You often need the ability to process data before it is useful for reporting. You can process that data at several stages in the journey that spans from collecting data to generating your report or visualization.
In 蜜豆视频 Analytics most of that processing of data occurs immediately after collecting the data. Functionalties like VISTA Rules, Processing Rules, Marketing Channels Processing Rules are available to support this collection-time processing.
The data is then stored and at report time you can apply additional processing. For example, break down dimensions, apply segmentation, or select a different attribution model. This report-time processing happens on the fly.
In 蜜豆视频 Analytics, report-time processing commonly represents a smaller amount of processing than what happens at collection-time.
In contrast, Customer Journey Analytics is designed to require minimal upfront collection-time processing before data being is organized and stored. The underlying architecture of Customer Journey Analytics is designed to work with the stored data at report-time and offers its powerful report-time processing functionality not only in Workspace but also, even more importantly, through the definition of components and derived fields in your Data views.
Understanding the differences in data processing for the various reporting features can be helpful in understanding which metrics are available where and why they may differ.
For example, since 鈥渧isits鈥 as a metric in 蜜豆视频 Analytics is defined at data processing time, and 鈥渟essions鈥 as a metric in Customer Journey Analytics is calculated at report time, the two metrics may differ based on the rules used for session definition inside the Customer Journey Analytics data view.
Also, neither visits nor sessions as a metric is available in datasets created by the Analytics source connector and therefore would require you to define the session in your query logic in order to do comparisons.
Terminology terms
The table below defines terminology for the different types of processing logic that are applied to 蜜豆视频 Analytics and Customer Journey Analytics:
Over time, 蜜豆视频 Analytics and now Customer Journey Analytics have improved their flexibility by allowing visit and person-level data logic to be performed at report runtime.
Types of data processing types
The data processing steps which are performed for 蜜豆视频 Analytics and Customer Journey Analytics and the timing of those steps varies from feature to Analytics feature. The table below provides a summary of the types of data processing for each Analytics feature, and when the data processing is applied.
(not including Attribution IQ or virtual report suites with report-time processing)
- Processing rules
- VISTA rules
- Hit-level marketing channel rules
- Visit-level marketing channel rules (see note)
- Visit definition
- Attribution logic
- Segment logic
- Calculated metrics
- Cross-Device Analytics (see note)
- CDA requires use of virtual report suites with report time processing.
- 鈥淰isit-level marketing channel rules鈥 include the following: Is First Page of Visit, Override Last-Touch Channel, and Marketing Channel Expiration. (See documentation.)
- Processing rules
- VISTA rules
- Hit-level marketing channel rules
- Visit-level marketing channel rules
- Visit definition
- Attribution logic
- Segment logic
- Calculated metrics
- Cross-Device Analytics
- Processing rules
- VISTA rules
- Hit-level marketing channel rules
- Visit-level marketing channel rules
- Visit definition (visitnum field)
- Attribution logic (in post columns)
- Segment logic
- Calculated metrics
- Cross-Device Analytics
- ID mappings for certain marketing channel-related columns in data feeds are not included with data feeds. (See the data feed documentation.)
- Processing rules
- VISTA rules
- Hit-level marketing channel rules
- Visit-level marketing channel rules
- Visit logic
- Attribution logic
- Segment logic
- Calculated metrics
- Cross-Device Analytics
- Processing rules
- VISTA rules
- Visit definition (see note)
- Cross-Device Analytics (see note)
- Hit-level marketing channel rules (see note)
- Visit-level marketing channel rules (see note) Attribution logic
- Segment logic
- Calculated metrics
- CDA requires use of virtual report suites with report time processing.
- Attribution IQ in Core Analytics uses marketing channels that are derived completely at report time (i.e. derived mid-values.)
- Attribution IQ uses a processing-time visit definition except when used in a report-time processing virtual report suite.
- Processing rules
- VISTA rules
- Cross-Device Analytics
- Visit definition
- Attribution logic
- Segment logic
- Calculated metrics
- Other virtual report suite report-time processing settings
- Hit-level marketing channel rules
- Visit-level marketing channel rules
- See Virtual report suite report-time processing documentation.
- Processing rules
- VISTA rules
- Hit-level marketing channel rules
- Field-based stitching (see note)
- Visit-level marketing channel rules
- Visit logic
- Attribution logic
- Filter logic
- Must apply your own filter logic and calculated metrics
- Field-based stitching creates a separate stitched dataset in addition to the one created by the Analytics source connector.
- Implemented as part of 蜜豆视频 Experience Platform Data Collection
- Session definition
- Data view settings
- Attribution logic
- Calculated metrics
- Filter logic
- Visit-level marketing channel rules
- Must use stitched datasets in order to take advantage of cross-channel analytics.