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A Guide to Customer Journey Analytics Data View Component & Global Filter Settings

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Employee

5/25/23

Introduction

Skillful configuration of the data view component and global filter settings is critical for building effective Data Views that enable insights into customers' journeys. Data views empower the Project workflow in the Analysis Workspace application of Customer Journey Analytics (CJA), turning it into a dynamic tool for users to analyze customer journeys within and across platforms.

This blog post provides a deeper dive into the overview covered in "A Guide to Understanding and Utilizing Customer Journey Analytics Data Views." In this document, I will provide additional context details around the choices for component and global filter settings within data view configuration. These choices can have important consequences for both reporting solution logic and user interface experience.

Component Settings

The component settings allow users to select which metrics and dimensions to include in their data views. This feature is powerful because it enables users to customize their data views to meet their specific needs. Users can display only the metrics and dimensions that are important to their data view and choose how to display these components, such as setting a custom name, description, or context labels. Of the highest consideration are decisions regarding the retroactive and non-destructive capabilities of component logic settings in a Data View. These capabilities provide unique solution advantages for altering the upstream base schema element settings at runtime of a report. To learn more about this, see the Data View capabilities documentation.

The configuration settings for component options will vary depending on whether the component type is set to metric or dimension. The individual component binary selection in this case will also determine its placement within the main component data view configuration settings. The configuration settings and options displayed on a per-component basis can be categorized into three levels based on their impact on data view, as applicable for metrics and dimensions. These settings levels are defined as follows as of May 2023:

  1. The data view configuration includes user interface settings that only affect how metrics and dimensions are presented within Customer Journey Analytics, without impacting their underlying processing logic or actual values. When managing a dataset, clear organization and rationalization are crucial. A useful tool for achieving this is a set of customizable settings on a data-view basis. These settings can assist users in navigating, sorting, and mentally organizing data work building blocks, such as metrics and dimensions, in an intuitive way. This, in turn, facilitates easier analysis and interpretation in Analysis Workspace. By utilizing these features, users can streamline their company's reporting and analysis workflow from ideation to presentation, making the most of the available datasets.
    1. Component name
    1. Description
    1. Context labels
    1. Hide component in reporting
  1. Data view settings also incorporate the Adobe Experience Platform schema base properties inherited from upstream dataset connections. These properties are fixed and non-configurable at the data view level. Even though these settings cannot be altered, they provide a significant frame of reference for the structure and lineage of the data from connection ingest into Customer Journey Analytics. The values can help establish context around the original intent and purpose of the data at the Adobe Experience Platform schema design layer.
    1. Schema field name
    1. Dataset type
    1. Dataset
    1. Schema data type
    1. Component ID
    1. Schema path
    1. Data usage labels
  1. The reporting logic settings of the configurable data view component carry the heaviest weight in terms of reporting layer properties and dataset interoperability. These settings are highly significant as they determine the level to which users can analyze, utilize, and rationalize data on a fundamental basis. In other words, data view administrators can customize the way in which data is analyzed, allowing users to gain more meaningful insights into their data. Decisions made regarding the configuration of these settings can have important consequences for both the reporting solution logic and user interface experience. Therefore, it is crucial to take the time to carefully consider and choose the most appropriate component settings when configuring a data view. By doing so, users can enhance their company's reporting and analysis workflow for Customer Journey Analytics.
    1. Component type
    1. Format (Metric Applicable Only)
    1. Set substring (Dimension Applicable Only)
    1. Behavior
    1. No value options (Dimension Applicable Only)
    1. Include exclude values
    1. Metric deduplication (Metric Applicable Only)
    1. Attribution (Metric Applicable Only)
    1. Persistence (Dimension Applicable Only)

    Keep in mind that certain component data view settings can be overridden in Analysis Workspace at the project level, such as the lookback window, metric attribution, and inclusion/exclusion of no value line items. However, other settings cannot be overridden, such as component type, metric format, data view name, and persistence allocation.

Global Filter Settings

Properly configuring the final data view filter settings is crucial. Global filter settings allow users to filter their data views based on various criteria, such as date range, defined filters, and session definition settings. For example, users can filter data by date range to focus on specific time periods. Custom data view global filters created by users are pre-applied to any report run in Analysis Workspace. A time period must also be specified for inactivity between events that will trigger a session to expire and a new one to begin. Additionally, users can optionally choose to force a new session to start when an event contains a specific metric. The global filter settings enable users to create highly tuned overarching parameters to govern their data views.

Conclusion

Users can create highly customized data views that offer insights into their customers' journeys by using the component and global filter settings effectively. This allows them to see which marketing campaigns or channels are most effective in driving conversions, or which content on their platforms is most frequently visited by customers.

The settings for the data view component and filter settings are critical features for establishing Customer Journey Analytics. By creatively utilizing these features, users can create data views that provide valuable insights into their customers' journeys. The data view configuration offers a high degree of freedom, allowing users to tailor their datasets to specific needs and requirements. This approach's flexibility encourages forward-thinking that can drive unique analytics solutions. These solutions can lead to a deeper understanding of customers and their needs, providing a competitive advantage. Overall, the ability to create customized data views that maximize the capabilities of component and global filter settings is an invaluable tool for any company looking to better understand and serve its customer base.