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 provides the interface that allows users to build, define, and manage a list of segments.
You can view 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.
You can reorder the list of segments alphabetically by Name and Status. Or, you can reorder the date Last updated. Quickly view which campaigns a segment is activated under Used in.
Segment tabs¶
After you click a segment on the Segments page, you can view insights about segments on the following tabs:
Summary tab¶
The Summary tab highlights important information about a segment, including:
How much opportunity does this segment have?
Which channels can I engage on?
What is the predicted revenue for this segment?
Use the information on the Summary tab to help determine the best way to initiate a marketing campaign.
Each Summary tab contains the following details:
The number of unique customers.
The number of customers who have been active within the last year.
The amount of revenue generated from these customers within the last year.
Revenue statistics, including historical revenue trends and a revenue tree.
The revenue tree shows the following segment insights:
Net revenue
Customers
Revenue per customer
Orders per customer
Average order value
Units per transaction
Average unit revenue
Note
Historical revenue represents the sum of order revenue for all customers who made at least one purchase during the previous year.
Tip
You can view the SQL query for each summary statistic by opening the menu and choosing View SQL.
Breakdown tab¶
The Breakdown tab contains insight charts for customer behaviors and customer attributes. You can ask questions to analyze customer demographics and identify target market segments:
What is the distribution of customers across categories?
What are potential customer groups for my marketing efforts?
These charts have a configurable date range and the displayed attributes charts are customizable. To customize the breakdown charts displayed on the Breakdown tab, click the Customize link, select up to six charts on the Customize Breakdown Charts window, and then click Apply.
Note
Compare by % of Purchasers, % of Revenue, or Revenue/Purchaser in the breakdown charts by selecting one of these options from the Compare by: drop-down menu.
Tip
You can expand a breakdown chart by clicking the icon and then clicking Expand.
Compare tab¶
The Compare tab shows how two or more segment statistics compare. You can ask questions that compare key metrics and identify shared audiences to identify new opportunities to reach customers.
What is the overlap if I compare multiple segments?
How do metrics like active customers, revenue, average revenue per customer, average units per order, and average order value compare across segments?
Note
Up to five total segments can be compared together.
You can identify overlapping customer groups by visually comparing up to five segments.
Customers tab¶
The Customers tab 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. You can download a csv file containing detailed information about each individual customer within the selected segment. This comprehensive dataset includes information such as:
Basic information like a customers email, address, and phone number.
Depending on your company’s PII restrictions, age group and birthday.
Other categories that are identified in your Customer 360 table.
Tip
You can customize the columns to display in order to only focus on certain attributes. You can also download the segment as a CSV file.
How segments work¶
The Segment Editor is the user interface for building segments. 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:
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The Segment Editor is available from two locations within Amperity:
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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:
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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:
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. |
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Segment insights show you answers to the following questions:
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: 
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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. 
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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:
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. |
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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. 
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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, Facebook Ads, Google Ads, Klaviyo, and The Trade Desk.
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 “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.
Inclusions and exclusions¶
Inclusions define the set of conditions that determine which customers will belong to an audience. When a customer matches the criteria defined for an inclusion, that customer will be included in the audience.
Exclusions define conditions that determine which customers will not belong to an audience. When a customer matches the criteria defined for an exclusion, that customer will be excluded from the audience.
Attributes¶
Attributes are selected from data tables that exist in your brand’s customer 360 database.
Tip
Amperity makes attributes available as standard output.
The following tables are standard output of Amperity. These tables (and the attributes within them) are always available to the Segment Editor:
Predicted Affinity (when predictive modeling is enabled for your tenant)
Predicted CLV Attributes (when predictive modeling is enabled for your tenant)
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.
Customer lists¶
Customer lists may be included or excluded. Customer lists can be any of the following: queries that have been made available to the Segments page, other segments that exist in your tenant, or lists of customers that have been uploaded to Amperity.
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:
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.
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:
Within a group of attributes
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.
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“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. |
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“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. |
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“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. |
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“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. |
Databases and tables¶
You can use any database table that is available to the Segments page to build attribute groups. The tables are shown in the bottom right corner of the Segment Editor.
You may change the selected database by choosing another one from the drop-down menu.
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.
SQL editor¶
The 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.
The Segment Editor has the following requirements:
The only field that can be returned by the
SELECTstatement is amperity_id.All conditions and values must be contained within a
WHEREclause.A
WHEREclause must use one of the following conditions:ANDorOR.
Example SQL segment
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%'))
)
)
)