Attributes

📄️ Attributes List

The Attributes screen provides an overview of the various attribute groups and individual attributes linked to a specific Data Layer. This interface is useful for monitoring and managing the data attributes within a system. The screen is divided into two primary views: Group and List, each serving different purposes.

📄️ Sample Attributes

In an effort to give users a better starting point, a few sample attribute-building ideas and details are contained within this article. The ideas for these attributes have been sourced from a number of use cases we've handled over the years and can be achieved within the confines of a sample dataset. Your use cases and data may be completely different, but the goal here is to get the creative juices flowing.

📄️ Creating Attribute using Attribute Builder

Creating a target audience begins with defining specific characteristics or behaviors known as attributes. In the Attribute Builder, you can group related attributes to create an attribute group. For example, you might have an attribute group named "E-commerce", which contains attributes like "cart\abandoned". "cart\add", and "Wishlist\_items".

📄️ Creating Attribute using Auto Extract

The auto-extract option allows attribute values to be automatically generated from distinct values from the selected source column instead of manually defining each attribute value.

📄️ Executing Attribute(s)

Once the attributes are defined, they can be executed through a job. The job can be run from either the Attribute List or the Attribute Builder page. This article will cover the following topics:

📄️ Attributes Result Tables

Utilizing the Audiences feature involves several steps to create and send audiences to downstream systems such as Facebook, Yahoo!, Google Analytics, and Nielsen. The high-level steps for defining attributes and using them to create audiences have been covered in previous articles.