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There are a number of filters that you can apply to customers to segment them. The table below describes all of the available filters.

Filter

Options

Description

What someone has done or not done

Started checkout
Started checkout value
Return cart
Return cart value
Ordered product
Ordered product value
Placed order
Placed order value
Fulfilled order
Fulfilled order value
Subscribed to List
Unsubscribed from List
Clicked Email
Delivered Email
Opened Email
Marked Email as Spam

This filter is one of the most popular filters to use. The filter allows you to look at the activity of the customer within the given time period.

If someone is or is not in a list

is in <list>
is not in <list>

Checks the customers list membership.

Loyalty point balance

is more than <number>
is less than <number>
is between <number> and <number>

Checks the loyalty points that the customer has earned. Useful to remind the customer that hasn’t purchased in a while that they have loyalty points to redeem.

Tags on someone

is tagged with <value>
is not tagged with <value>

Checks if the tags on the customer profile.

Properties about someone

text properties
equals
doesn’t equal
contains
doesn’t contain
is in
is not in
starts with
doesn’t start with
end’s with
doesn’t end with
is set
is not set
number properties
equals
doesn’t equal
is at least
is more than
is less than
is at most
date properties
is in the last
is at least
is at most
is in between
is in the next
is before
is after
is today
is in this month
is in the month of
boolean properties
is true
is false

Comparison operators to properties set on the customer profile. Each of the four different types of properties have their own comparison options.

If someone is or is not within the EU

is in
is not in

Someone’s proximity to a location

is within
is not within

Determines if the customer is within a certain proximity to a given location. Useful to targeting customers within reasonable travel distance of an in person event.

Analytics about someone

Average order value
Average days between orders
Historical customer lifetime value
Historical number of orders

Overall analytic metrics about the customer.

Multiple Filters with Boolean Logic

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Ranking is especially powerful when creating a segment to populate a Facebook custom audience. You have the ability to select the top 25% of your customers that purchased within the last year based upon their total order value. As Facebook finds you more customers of this quality, your average customer value would increase over time and the segment would dynamically adjust to include only the cream of the crop.

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