Create Data Views in Customer Journey Analytics
Learn how to create data views from your connections in Customer Journey Analytics. Data views are flexible interpretations of data in a connection. You can create data views with different settings for visit timeout and dimension attribution models, and much more.
Basic configuration for Data Views in Customer Journey Analytics
Once you have created a connection in ÃÛ¶¹ÊÓƵ Customer Journey Analytics to data sets in the ÃÛ¶¹ÊÓƵ Experience Platform, you need to create a Data View for that Connection, so that you can use the data in Analysis Workspace on Platform. This video walks you through the basic configuration of a Data View.
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Configuring component settings in Data Views
In this video we'll walk through a few of the basic component settings that you'll want to configure for each of the components (metrics and dimensions) when you are setting up a Data View in Customer Journey Analytics.
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Component type settings in Data Views
When configuring components in a Data View in Customer Journey Analytics, you can choose whether a field should be a metric or a dimension. In many cases, strings should be dimensions and numbers should be metrics. However, there are some great use cases to switch it up. Take a look!
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Create derived fields in Customer Journey Analytics
Derived fields is a powerful feature that allows users to create complex data manipulations on-the-fly through a customizable rule builder and then have the logic apply retroactively to their reporting, saving significant time in ensuring data is in a usable format for reporting, analysis & action.
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Adjust metrics by using the math function in derived fields in Customer Journey Analytics
Explore the potential of using Math functions for creating derived fields in Customer Journey Analytics in this video tutorial. Learn to adjust metrics by removing unwanted components such as tax from totals, and understand the advantages of using derived fields over calculated metrics, including exclusive data view features like de-duplication, bucketing, and attribution.
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Unlock advanced insights with the 'Next or Previous' function in derived fields
Discover how to use the 'Next or Previous' function in Customer Journey Analytics to create complex derived fields that enhance data analysis. This tutorial guides you through the process of setting up a new dimension that concatenates marketing channel values at the user level, enabling deeper insights into marketing strategies and revenue generation.
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Formatting metrics in Data Views
In this video you will learn about the options for formatting metrics in the component screen of Data View configuration. We will also discuss a couple of tips that can help you get more out of your components.
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Include or exclude metric values in Data Views
In this video, learn how to create and configure new metrics that are subsets of other metrics, as well as the use cases that can make this a very powerful analysis tool in Data Views.
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Creating value buckets in Data Views for analysis
When configuring a Data View in Customer Journey Analytics, you can set a numeric dimension to be lumped into defined buckets, so that you can limit the number of items available for the table to ranges of numbers (very cool). This video walks you through configuration of this feature.
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Attribution Settings in Data Views
Each dimension should have an allocation setting (to decide which value gets credit for conversion) and an expiration setting (how long the value persists), so that the system knows how to assign value to the dimension values. Similarly, and working together, metrics should have an attribution model and lookback window set as well. This video walks you through setting these all-important settings.
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