Audience Filter overview

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The Audience Filter module lets you quickly select target marketing audiences that meet specific size and filtering criteria. These audiences provide a foundation for future outreach. An audience is a collection of users who meet specific rules. You can then use these audiences for insight analysis, to push marketing content, or to send them to Data Bank, Damengpan, or Kafka.

The User Insights module provides the following ways to create audiences:

  • Audience Filter: Also known as audience selection, this method creates an audience by filtering users from a dataset who meet specific conditions.

    • Tag Filtering: Filters audiences based on user tag datasets, including custom tag datasets. This method selects an audience that meets specific tag value requirements. For example, you can filter for users where Province = Zhejiang and Gender = Female.

    • RFM Model Filtering: Filters audiences based on the RFM model. You can filter by score or customer type.

    • AIPL Model Filtering: Filters audiences based on the AIPL model. You can filter by customer type or by stream.

    • Behavior Filtering: Filters audiences based on behavioral datasets. This method selects an audience with specific behavioral features. For example, you can filter for all users who purchased Product A at an offline outlet in the last 30 days.

    • Cross Filtering: Creates an audience by calculating the union or intersection of the results from two or more of the preceding filter types. This is suitable for more complex selection scenarios. For example, you can filter for all female users from Zhejiang who purchased Product A at an offline outlet in the last 30 days.

  • The Audience Management page provides the following ways to create audiences:

For other audience creation methods, see What are other ways to generate audiences besides using Audience Filter?