About segments

A segment defines a specific attribute profile that can be used to initiate marketing campaigns using the list of customers that match that profile.

Use the Segment Editor to build any audience using a series of drop-downs and picklists.

As you define the attribute profile for an audience be sure to refresh segment insights to see how many customers match your audience and to see how much value they bring to your business.

When the segment is ready, activate it, and then use it use it in a campaign to send to your preferred destinations for customer activation.

About the Segments page

The Segments page contains a list of active segments along with recommended segments highlighted across the top of the page.

Click Create Segment to open the Segment Editor. Build your segment using a series of drop-downs and picklists. Refresh segment insights to see how many customers match and to see how much value they bring to your brand. Activate the segment when you’re ready to use it in marketing campaigns.

Summary page

The Summary page highlights the most important information about a segment, including:

• How much opportunity does this segment have?

• Which channels should I engage on?

• What is the predicted revenue for this segment?

Use the information on the Summary page to help determine the best way to initiate a marketing campaign.

Each Summary page contains the following details:

1. The number of unique customers.

2. The number of customers who have been active within the last year.

3. The amount of revenue generated from these customers within the last year.

4. The number of customers who are reachable.

5. Revenue statistics, including historical revenue and predicted revenue trends.

   Tip

   Historical revenue represents the sum of order revenue for all customers who made at least one purchase during the previous year.

6. The channels through which this segment has customer opportunity.

7. Segment insight charts for customer behaviors and customer attributes. These charts have a configurable date range and up to six may be selected. Click the Actions menu, and then select Customize charts to choose up to six charts for customer behaviors and for customer attributes.

8. The list of customers who belong to this segment.

How segments work

The Segment Editor is the user interface for building segments in AmpIQ. This editor uses a series of drop-downs, picklists, conditions, and values to define an attribute profile. Refresh segment insights to see how many customers match the profile, and then activate it as a segment.

The Segment Editor is available from the Segments page. Click Create Segment from the Segments page to open the editor, and then start building your segment.

Follow this sequence when building a segment:

	The Segment Editor is available from two locations within Amperity: When adding an audience from the Segments page. The Create Segment button in the top right corner of the page opens the Segment Editor. When adding a sub-audience from within the campaigns editor. The Add sub-audience link opens a version of this editor—called Audience Builder—that does not contain segment insights.
	You may use any table in your customer 360 database to build an audience or sub-audience. Your customer 360 database should already be selected for you (by default), though it is possible to have more than one 360 database that is available to your Segment Editor. Expand each of the table rows to see the attributes that are available from that table. Open the Data Explorer to view detailed information about every table (including tables not made available to the Segment Editor) and every attribute, including examples of the values they contain. What are the standard tables for building an audience? Amperity provides the following tables as standard output: The Customer 360 table contains customer profile data — names, addresses, email addresses, phone numbers, and so on – summarized by unique customer. The Unified Transactions table contains order-level details for a transaction. The Unified Itemized Transactions table contains line-item and product catalog details for a transaction. The Transaction Attributes Extended table contains calculated attributes that are built from order- and item-level details in transaction tables.
	Start building your segment by choosing an attribute. The attributes that you choose to add to your segment will depend on the goals for your marketing use case. For example, maybe you want to start building out a churn prevention campaign that uses predicted lifecycle status as your starting point. The Predicted Lifecycle Status attribute helps you identify the individual stages within a churn prevention campaign to which your customers are predicted to belong. Click Add attribute to open the attributes menu, find the Predicted CLV Attributes table, and then choose the Predicted Lifecycle Status attribute. There are six possible stages for predicted lifecycle status, so choose the “is in list” operator, and then select “active”, “cooling down”, and “at risk”: After you add an attribute to your segment, click the Refresh button located on the right side of the Segment Editor to see how many customers are in your segment, how much they spent in the past year, how many are active, and how many of them should belong to a future campaign. What types of attributes can you choose? You can choose attributes the following categories: Tables in your customer 360 database. These include all standard output tables and may include custom tables you have added to Amperity. Standard output tables are always available. Purchase behaviors that combine your customer’s interaction histories with your brand with your brand’s product catalog. Purchase behavior attributes are always available. Custom tables built in the Queries page that are made available to the Segment Editor. Files that have been uploaded by you directly to the Segment Editor. These attributes are only available when files have been uploaded. Add attributes to your segment by clicking Add attribute, choosing a source (table, purchase behavior, custom table, or uploaded file), and then selecting an attribute. Some attributes, such as those that have “true” or “false” values will ask you to pick a value right away. Most attributes, such as those with string values, dates and times, amounts, and quantities, have additional fields that are available after the attribute is added to your segment.
	Segment insights show you answers to the following questions: How many customers are in your segment? How many of these customers have been active in the past year? How much did these customers spend in the past year? How many of these customers have a contactable email address, phone number, or physical address? When you start building a segment, the values for segment insights represent 100% of your customers and revenue across all categories. As you refine your segment by adding more attributes you can use the Refresh button to update the answers to those four questions. For example:
	Add as many attributes to your segment as you need. For example, to continue building out a churn prevention campaign, in addition to knowing if your customers are “active”, “cooling down”, and “at risk”, maybe you want to know which of those customers have made a purchase during the previous 3 months. Use the Has Purchased purchase behavior attribute to filter the “active”, “cooling down”, and “at risk” customers to those who purchased only 1 pair of socks within the previous 3 months: and then refresh segment insights.
	When you are done building your segment, click the Save As button in the top right corner of the Segment Editor. Give your segment a name that clearly describes the purpose and audience type for the segment. Tip Use good naming patterns to ensure that you can always find your segments when you need them. Add details like “historical”, “daily”, or “test” as appropriate. Be sure to include the brand name and/or the region name if you have multiple brands or have multiple regions. Some examples: “Birthdays_Under_40_CA” “Birthdays_Under_40_NY” “High_AOV_Active_Loyal” “High_CLV_Historical” “Acme_Daily_Churn” Prefix a segment that is located in a folder with that folder name as often as possible. For example, if you have a folders named “Braze” and “TikTok” use segment names like “Braze_Birthdays_Under_40_CA” and “TikTok_Birthdays_Under_40” for all segments that exist within those folders.
	After your segment is saved the Segment Overview page opens and shows additional details, such as historical and predicted revenue, the percentage of customers that are reachable by email, by phone, on Facebook, and customer trends, such as purchases by channel, revenue by lifetime spend.

Segment names

A good segment name is clear and concise, is not longer than necessary, uses patterns to help lists of segments stay organized, and considers how it might be represented in downstream workflows, such as lists of segments in the Campaigns page in Amperity, but also external systems such as Braze, Campaign Monitor, Facebook Ads, Google Ads, Klaviyo, and Mailchimp.

Important

Users of downstream systems are often not the same set of users who configure and manage segments in Amperity.

If you send a segment named and if you send them a segment named “Untitled segment (43) - 2021-08-13-09-34-35” your downstream users might not know what to do with it.

Be sure to follow good naming patterns to ensure that downstream users can always find your segments when they need them. Add details like “historical”, “daily”, or “test” as appropriate.

Be sure to include the brand name and/or the region name if you have multiple brands or have multiple regions.

Some examples:

• “Birthdays_Under_40_CA”

• “Birthdays_Under_40_NY”

• “High_AOV_Active_Loyal”

• “High_CLV_Historical”

• “Acme_Daily_Churn”

Prefix a segment that is located in a folder with that folder name as often as possible.

For example, if you have folders named “Braze” and “TikTok” use segment names like “Braze_Birthdays_Under_40_CA” and “TikTok_Birthdays_Under_40” for all segments that exist within those folders.

If your downstream systems will have data from non-Amperity systems, consider using Amperity as the first prefix: “Amperity_Birthdays_Under_40_CA”.

Use leading zeroes if a sequential numbering system is a prefix. For example: 0001, 0002, 0003, …0100 is preferable to 1, 2, 3, …100. This will help ensure that your segments are ordered sequentially in the Amperity Segments page and downstream systems.

Attributes

Attributes are the fields in your data tables that your brand uses to create segments, define audiences, and build campaigns.

Tip

Amperity makes attributes available to you as part of standard output.

The following tables are standard output of Amperity. These tables (and the attributes within them) are always available to the Segment Editor:

• Campaign Recipients

• Customer Attributes

• Customer 360

• Predicted Affinity (when predictive modeling is enabled for your tenant)

• Predicted CLV Attributes (when predictive modeling is enabled for your tenant)

• Transaction Attributes Extended

• Unified Itemized Transactions

• Unified Transactions

This topic collects all of the attributes that are available in standard output into a single topic. It is organized alphabetically by table, and then within each table attribues it is organized alphabetically by attribute name.

Purchase behaviors

Marketers use purchase activities to gather information about how customers are (or are not) interacting with their brands and to build audiences around ideas like first orders, repeat orders, most frequently ordered, total value or orders, who has purchased and who has not purchased.

You can use any of the following purchase behaviors in your segments:

• First order

• Has not purchased

• Has purchased

• Most frequent order

• Repeat order

• Total value of orders

Note

Your tenant must use Amperity standard field names, including for your product catalog, to use purchase behaviors in your segments.

Segment insights

Segment insights show you answers to the following questions:

• How many customers are in your segment?

• How many of these customers have been active in the past year?

• How much did these customers spend in the past year?

• How many of these customers have a contactable email address, phone number, or physical address?

When you start building a segment, the values for segment insights represent 100% of your customers and revenue across all categories.

As you refine your segment by adding more attributes you can use the Refresh button to update the answers to those four questions.

For example:

Segment insights include the following categories:

• Unique Customers shows the number of unique customers who are in the segment, where a unique customer is represented by a unique Amperity ID.

• 1-year Active Customers shows how many unique customers have made a purchase within the past year.

• 1-year Segment Revenue shows the total revenue for all purchases made by active customers within the past year.

• Reachable Customers shows the number of unique customers who have at least one contactable email address, phone number, or physical mailing address.

Note

Segment insights are available when your customer 360 database contains certain tables.

• Unique Customers, 1-year Active Customers, and 1-year Segment Revenue require access to the Transaction Attributes Extended and Customer 360 tables.

• Reachable Customers requires access to the Customer Attributes table.

Databases and tables

You can use any database table that is available to the Segments page to build attribute groups. All of the tables in the currently-selected database are available from the drop-down menu in each attribute group and are shown in the bottom right corner of the Segment Editor.

1. You may change the selected database by choosing another one from the drop-down menu.

2. The list of tables is refreshed to show the tables in that database.

Important

Tables must be configured to be available to the Segments page. This must be done by a member of your team who manages databases and tables from the Customer 360 page.

AND vs. OR

AND and OR are used in SQL languages to specify how results should be filtered when more than one condition is present.

• Use AND to return a smaller (and more specific) list of customers. A customer must match all conditions to belong to the list.

• Use OR to return a larger (and more broad) list of customers. A customer may match any condition to belong to the list.

Amperity uses AND and OR to help you choose which type of behavior – larger audiences or smaller audiences – you want to use in your segment.

The AND and OR conditions may be set in two locations:

1. Within a group of attributes

2. Between groups of attributes

The default is AND. Use the slider to switch to OR.

How AND and OR work

The following examples describe how AND and OR conditions work.

	“I want to build an audience that returns customers who have an email address.” In this example, there is only one condition. The audience that is returned contains only customers who have an email address.
	“I want to build an audience that returns customers who have an email address AND customers have opted in to receiving email messages from my brand.” In this example, the audience that is returned – shown as the darker color – is smaller because only a subset of customers for whom you have email addresses have opted in to receiving email messages from your brand.
	“I want to build an audience that returns customers who have an email address OR customers who have phone number.” In this example, your audience grows larger because both conditions are met: email address or phone number. This is shown as both colors and the total audience is the overlap of both conditions.
	“I want to build an audience that returns a customer’s email address OR a customer’s phone number AND customers have opted in to receiving messages from my brand from to their email address OR phone number.” This audience has two groups of attributes: email addresses OR phone numbers AND opt-in status for email addresses OR phone numbers. The first group of attributes – email addresses or phone numbers, as shown in the darker color – should make your audience larger. Few data sets have a perfectly matching set of email addresses and phone numbers across all customers. The second group of attributes – opt-in status for email addresses or phone numbers, as shown in the lighter color – should also be larger as a group than by themselves. You should expect the number of customers who have opted in to receive email or SMS communications to be smaller than the number of customers who have provided email addresses or phone numbers to your brand. These two groups are in-between an AND condition within your segment: email address or phone and opt-in status for email address or phone. Your audience then grows smaller because only a subset of customers for whom you have email addresses or phone numbers have opted in to receiving email or SMS messages from your brand. The smaller audience of opted-in customers for whom you have email addresses and phone numbers is shown by the darker color.

SQL editor

The SQL Segment Editor is an optional interface that allows you to build an attribute profile with SQL. Start with a SELECT statement that returns the Amperity ID, and then apply a series of WHERE statements to define one (or more) attribute groups that match specific conditions and values.

Note

The SQL Segment Editor is an optional interface that allows you to build an attribute profile using Presto SQL. Start with a SELECT statement that returns the Amperity ID, and then apply a series of WHERE statements to define one (or more) attribute groups that match specific conditions and values.

There SQL Segment Editor has the following requirements:

1. The only field that can be returned by the SELECT statement is amperity_id.

2. All conditions and values must be contained within a WHERE clause.

3. A WHERE clause must use one of the following conditions: AND or OR.

Example segments

For example, a segment that uses the OR condition to return customers whose first name begins with “Mi”, last name begins with “Smi”, and who reside in California:

SELECT
  "amperity_id"
FROM
   "Customer_360"
WHERE
  (
    (LOWER("given_name") like '%mi%')
     OR LOWER("state") = 'ca'
     OR (LOWER("surname") like '%smi%')
  )

The following example is identical to the previous example, but shows each condition in its own WHERE clause, using UNION ALL between each clause to group the results together:

SELECT
  "amperity_id"
FROM
   "Customer_360"
WHERE
  (
    (
      "amperity_id" IN (
        SELECT
          "t0"."amperity_id"
        FROM
          "Customer_360" "t0"
        WHERE
          ((LOWER("t0"."given_name") like '%mi%'))
        UNION ALL
        SELECT
          "t1"."amperity_id"
        FROM
          "Customer_360" "t1"
        WHERE
          (LOWER("t1"."state") = 'ca')
        UNION ALL
        SELECT
          "t2"."amperity_id"
        FROM
          "Customer_360" "t2"
        WHERE
          ((LOWER("t2"."surname") like '%smi%'))
      )
    )
  )

Segment overview

A segment overview highlights the most important information about a segment, including:

• How much opportunity does this segment have?

• Which channels should I engage on?

• What is the predicted revenue for this segment?

Use the information on the segment overview to help determine the best way to initiate a marketing campaign.

Summary

Each segment summary contains the following details:

1. The number of unique customers in this segment.

   Note

   In order display unique customers in this segment, the Unique Customers insights card queries Amperity IDs to match them up with each unique customers.

2. The sum of order revenue in this segment over the previous 12 months.

   Note

   In order to display the total revenue for this segment over the past 12 months, the 1-Year Active Customers insights card queries data from transaction attributes, total revenue, and Amperity IDs.

3. The total order revenue for all unique customers in this segment who have ordered in the previous 12 months.

   Note

   In order to display the total revenue for this segment over the past 12 months, the 1-Year Segment Revenue insights card queries data about transaction attributes and total revenue.

4. The number of reachable customers in this segment.

   Note

   In order to display reachable customers in this segment, the Reachable Customers insights card customer queries customer contact information, including at least one phone number, email address, and/or physical mailing address.

5. Revenue statistics, including historical revenue and predicted revenue trends.

6. The channels through which this segment has customer opportunity.

7. The list of customers who belong to this segment.

Customer details

The Customers page shows the all data for all of the customers in this segment as a series of columns pulled from various tables in your Customer 360 database.