After reviewing this page, you should be able to answer the following questions:

Audiences have two types of filter criteria to shape your audience for what you need: library and filter criteria.

The audience library has pre-set filter options that you can use as a base or on their own, and add additional filter criteria, such as frequency caps.

Audience filter criteria can be used with a library filter or on its own.

Both Email and SMS Eligibility identify a customer's subscription status and are used to preview audience segmentations.

The statuses determine which customers meet email eligibility criteria for certain email campaign types and ensure compliance with GDPR, CCPA, CAN-SPAM, and other consumer privacy laws.

The statuses are:

Customer attributes are details about a customer's profile that are collected using a site campaign, Bluecore integration, or data import.

You can collect as many attributes as you need, such as loyalty status, as well as the standard customer profile fields:

Customer date attributes can reference specific or relative dates so you can send more precise campaigns based around birthdays, loyalty membership date, or other dates captured on the Customer Profile.

For example, you could send out a birthday campaign the month before a customer’s birthday, a birthday email on their actual birthday, and a follow-up one month after.

Additional date filters include but are not limited to:

Audiences can be segmented based on customer behaviors, like their engagement with email and/or mobile or website product interactions.

There are standard behaviors that you can use, and custom behaviors can be created as needed.

Product filters

Additional product attributes can be added as filters to narrow down which products a customer interacted with, for example by category or by color.

There are standard product fields that are on all products that can be leveraged for further filtering:

Some product filters, such as price or out of stock status, can be refined to use a time frame so it refines the audience by the value is at the time of the customer behavior event or at the time of the campaign send.

If you need to capture more product attributes, you can create custom ones.

Channel preferences uses a predictive, machine learning model to filter audiences down by which customer prefers email, mobile, shows no preference, or whose preference is unknown.

See email or mobile channel preferences for more information.

The static email list allows you to select a previously uploaded email list.

The predicted customer lifetime value (PCLV) targets customers based on the predicted total amount they may spend in the next two weeks. You can filter your audience by the top percentage, percentage range, or the bottom percentage.

The lifecycle stage filters customers down to their predicted lifecycle stage that’s based on their past activity. You can choose from the following lifecycle stages:

Customers can be targeted by how likely they are to take the following actions in the next two weeks.

Using product preferences constructs an audience based on predictions about the products that customers are interested in.