How do I create and use segments?

Segments are created based on subscriber data that is stored in your account. This includes list data imported to your account or submitted by subscribers themselves through a form, as well as campaign data from previously sent emails.

A segment can only be attached to one subscriber list, but you can create as many segments as you like for a list. The segments themselves can be built on one rule, or multiple rules, as we'll explain on this page.

On this page:

Creating rules to build a segment

To set up a new segment, open the subscriber list you want to work with and click Segments in the right sidebar. Then on the "Segments" page, click Create a new segment.

Next, use the Define a rule based on menu to select the data type for your first rule:

The menu options include:

  • Subscriber details – Includes the default fields, name and email, and the date subscribed
  • Custom fields – Displays every custom field you have set up for the list, if you have any.
  • Campaign activity – Use this to build a segment based on campaign data. For example, group all subscribers who did not open a specific campaign.

When you've selected a data type you then need to apply a condition to it. Each data type has a set of conditions that can be applied to it, to create the rule. For example, our "Gender" custom field shown below is a text field. The conditions available for text fields are:

  • matches exactly
  • does not match exactly
  • is provided
  • is not provided
  • contains
  • does not contain
  • starts with
  • does not start with
  • ends with
  • does not end with

Note: The "matches exactly" condition is not case sensitive, meaning "male" is equivalent to "Male".

Not all conditions are available for each data type. Here's another example where Campaign activity > Specific campaign has been selected to build a rule based on campaign data:

The conditions available for campaign activity data are:

  • was opened
  • was not opened
  • had any link clicked
  • had a specific link clicked
  • was opened with no links clicked
  • was opened and did not have a specific link clicked

Either of the examples pictured above could be useful segments, even though they only contain one rule:

  • Segment example one: group all subscribers who are male.
  • Segment example two: group all subscribers who did not open the "Feb Widget News" campaign.

If your segment only requires one rule check out the following section on testing segments then, if you like, jump ahead to read about using segments when sending campaigns.

Testing segments

When you have finished adding the rules to build your segment, give it a name that will be easy to recognize later, then click Save and preview. This creates the segment of people on the subscriber list who match the criteria set by your rules, or rule.

The total number of active subscribers in the segment will be displayed on the page. You'll also get a sample of some of those subscribers, as shown here:

It's a good idea to check that the segment includes the subscribers you expect it to. Here are a few ways that you can check this:

  • Click a sample subscriber's email address to open their subscriber snapshot, where you can check to see if their field values and attributes fit the segment.
  • Use the search tool above the list of sample subscribers to check for people who should be in the segment, based on the segment rules.
  • Click the Export segment button, next to the search box, to download a CSV file containing all subscribers in the segment.

Note: Campaign activity data cannot be downloaded in an "Export segment" file. To check if a segment based on campaign activity is correct, use one of the first two methods listed above.

Connecting rules in a segment

To create a segment with more than one rule, you need to connect the rules by choosing AND or OR every time you add a new rule, as shown here:

In the example above we've selected AND to add the next rule. This generates a new row to build the rule, starting with the Define a rule based on menu to select another data type.

It doesn't have to be a different data type. You can choose the same data type and apply a different condition to it. For example, a segment of people aged 25 to 35 can be created using two rules based on an "Age" custom field.

To set this up you would apply a "greater than" condition to the first rule with a value of 24, AND a "less than" condition to the second rule, with a value of 36:

When to use AND versus OR

You can connect rules in a segment using both AND and OR, but first, this is how to use one or the other:

  • Use AND to connect rules when you want to group subscribers who match all of the rules in your segment.
  • Use OR to connect rules when you want to group subscribers who match any of the rules.

Rules connected by AND

Here is the age segment referenced earlier with some extra rules added that are also connected by AND:

This segment is to group 25 to 35-year-old women in Detroit. To fit the segment, subscribers must be: older than (greater than) 24 AND younger than (less than) 36 AND of the female gender AND living in Detroit.

Rules connected by OR

Here's a segment containing three rules based on the custom field "Color preference", that are connected by OR: 

Assuming each one of these colors is a preference of at least one subscriber, this segment would contain some subscribers who like purple, some who like red and others who prefer yellow.

A broader target audience can make it difficult to focus campaign content but the same type of segment would be ideal for other purposes. For example, a conference being held in Detroit, Cincinnati and Chicago could be promoted only to subscribers who live in those cities.

Rules connected using AND and OR

For this example, let's say the owner of a national franchise wants to email store managers and assistant managers about some training workshops happening in their area.

The franchise owner creates a segment containing rules connected by AND and OR:

To fit this segment, subscribers must be a manager OR assistant manager AND work at a store in the region of Subiaco OR Jolimont OR Churlands.

Using segments when sending campaigns

When a segment is created it's added to the list of recipients that you choose from when sending a campaign. So instead of sending to an entire list you can select one or more segments to send to. Or, you may want to exclude a segment instead.

Use case:

A new payment method is introduced for customers on monthly billing subscriptions. The service provider wants to notify all customers who pay monthly, excluding the newest customers because they were set up on the new payment system.

Example segment:

The first rule groups all subscribers who pay monthly, and the second rule narrows the search so the segment only finds monthly payers who subscribed after the new payment system was launched:

The email about payment changes is sent to the entire list of customers, excluding the "New monthly customers" segment:

This would be an example of a segment you might want to delete after you've used it. The following section explains how to delete segments.

Checking, editing or deleting segments

To view all segments that have been created for a list, open the relevant subscriber list and click Segments in the right sidebar.

To delete a segment you no longer need, hover your cursor over the segment row, then click the trash can icon that appears on the right:

Note: Deleting a segment will not affect anything else in your account. Subscribers who were in the segment will still be active on your list and subscriber data will be exactly the same.

To edit or view a segment, click the segment name on your "Segments" page, pictured above, to open it. If you need to delete one or more rules from a segment, just hover your cursor over the rule row, then click the trash can icon that appears:

 

Full list of conditions for each data type

Each data type has a set of conditions that can be applied to it, to create a rule. Not all conditions are available for every data type. Below is the complete list of data types you can base a rule on, followed by the conditions you can apply to it.

Data type: email address

Conditions available:

  • contains
  • does not contain
  • matches exactly
  • does not match exactly
  • starts with
  • does not start with
  • ends with
  • does not end with
Data type: name

Conditions available:

  • matches exactly
  • does not match exactly
  • is provided
  • is not provided
  • contains
  • does not contain
  • starts with
  • does not start with
  • ends with
  • does not end with
Data type: date subscribed

Conditions available:

  • is before
  • is after
  • equals
  • does not equal
  • is on or before
  • is on or after
  • is between

Note: The "is between" condition is exclusive of the dates selected to create a rule. For example, a rule to segment people who subscribed between the 15th and 25th February will include anyone who subscribed from the 16th-24th February. This also applies to the date field data type.

Data type: text field

Conditions available:

  • matches exactly
  • does not match exactly
  • is provided
  • is not provided
  • contains
  • does not contain
  • starts with
  • does not start with
  • ends with
  • does not end with
Data type: numeric field

Conditions available:

  • matches exactly
  • does not match exactly
  • is provided
  • is not provided
  • greater than
  • less than
  • greater than or equal to
  • less than or equal to
  • is between
Data type: date field

Conditions available:

  • is before
  • is after
  • equals
  • does not equal
  • is provided
  • is not provided
  • is on or before
  • is on or after
  • is between
Data type: campaign activity

Conditions available:

  • Specific campaign – was opened
  • Specific campaign – was not opened
  • Specific campaign – had any link clicked
  • Specific campaign – had a specific link clicked
  • Specific campaign – was opened with no links clicked
  • Specific campaign – was opened and did not have a specific link clicked
Data type: multiple option custom fields

Conditions available:

  • matches exactly
  • does not match exactly
  • is provided
  • is not provided