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.

About the Segments page

The Segments page provides the interface that allows users to build, define, and manage a list of segments.

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.

Recommended segments

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

Configure recommended segments

Up to five segments may be configured to show in the list of recommended segments. (Ask your Amperity representative to configure the list of recommended segments for your tenant.)

	From the Segments page, under Recommended segments, click Configure. This opens the Configure recommended segments dialog box. For each recommended segment, use the drop-down list to choose a segment and then choose an icon.
	Up to five recommended segments may be configured.
	When your tenant has more than one database, you can select the list of recommended segments for each database. From the Segments page, you can switch between the lists of recommended segments by choosing a database from the “Showing segments for …” drop-down.

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.

Customers page

The Customers page shows the columns and tables from which customer data for this segment is available.

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.

Segment attributes

You can add attributes to your segment by selecting individual attributes from tables or by selecting from a series of pre-configured behavioral attributes.

Conditions

An attribute condition defines how results from a column in a data source will be returned.

For example: From your customer 360 table, return all customer records that contain email addresses that are similar to “gmail.com”. The data source is your customer 360 table, the attribute is the email field in that table, and the is like condition allows you to use “gmail.com” to look for values that contain “gmail.com”, and then return a list of customers who have “gmail.com” in their email address.

In SQL, an condition is expressed using the WHERE clause. The following example returns a list of customers who have “gmail.com” in their email address:

SELECT
  email
FROM
  Customer360
WHERE email LIKE "gmail.com"

In the Segment Editor you define conditions using a series of picklists that do not require knowledge of SQL or how to define a WHERE clause:

The list of conditions that are available to an attribute in the Segment Editor varies, with each list depending on its data type:

• Boolean

• Date

• Datetime

• Decimal

• Integer

• Relative dates

• String

Note

This topic is a reference for all conditions that are available to all attributes and is organized alphabetically by data type, and then by condition. This topic does not contain specific recommendations for specific attributes (or attribute groups). Refer to the individual attribute reference pages to learn more about the set of conditions that are available, including recommended conditions and examples of using them.

About NULL and not NULL values

A field with a NULL value is a field with a value that does not exist.

A NULL value is different than a value of zero, a blank value, or a value that contains only spaces. An attribute can only have a NULL value if it remained empty after the record was created.

For example, if you have 100 customers, 99 of which have provided a value for their phone number (even if some of those phone numbers are invalid phone numbers), 1 of which has not provided any value at all. The customer record that does not have a phone number is empty and is a NULL value.

Conversely, a field with a value that is not NULL is a field with a value that exists, including values of zero, blank values, and value that contain only spaces.

Using the 100 customers and their phone numbers example, Amperity would return 1 record when the “is NULL” condition is used and 99 records when the “is not NULL” condition is used, even if 2 of them contained spaces instead of numbers and 4 of them were “555-555-1234”.

Boolean conditions

A Boolean condition represents true and false outcomes, such as “Has this person purchased more than once?” The answer is “Yes” or “No.”

The following conditions are available to all attributes with the Boolean data type:

Operator	Description
is false	false returns customer records that are “false”.
is NULL	is NULL returns customer records that do not have a value. A record that does not have a value cannot be “true” or “false”.
is NOT NULL	is not NULL returns customer records that have a value. A record that has a value is either “true” or “false”.
is true	is true returns customer records that are “true”.

Date conditions

A Date data type represents a day, a month, and a year. For example: a birthdate.

A Date data type accepts YYYY-MM-DD.

The following conditions are available to all attributes with the Date data type:

Operator	Description
is	is returns customer records with activity that matches the specified calendar date.
is after	is after returns customer records with activity that occurred after the specified calendar date, not including the specified date.
is before	is before returns customer records with activity that occurred before the specified calendar date, not including the specified date.
is between	is between returns customer records with activity that is between the specified calendar dates, not including the specified dates.
is not	is not returns customer records with activity that does not match the specified calendar date.
is not between	is not between returns customer records with activity that is not between the specified calendar dates, not including the specified dates.
is not NULL	is not NULL returns customer records that have a value.
is NULL	is NULL returns customer records that do not have a value.
is on or after	is on or after returns customer records with activity that occurred on or after the specified calendar date, including the specified date.
is on or before	is on or before returns customer records with activity that occurred on or before the specified calendar date, including the specified date.

Datetime conditions

A Datetime data type represents a date and time combination. For example: a date and time at which a customer made a purchase.

A Datetime data type accepts “YYYY-MM-DD hh:mm:ss”.

The following conditions are available to all attributes with the Datetime data type:

Operator	Description
is	is returns customer records with activity that matches the specified calendar date and time.
is after	is after returns customer records with activity that occurred after the specified calendar date and time, not including the specified date and time.
is before	is before returns customer records with activity that occurred before the specified calendar date and time, not including the specified date and time.
is between	is between returns customer records with activity that is between the specified calendar dates and times, not including the specified dates and times.
is not	is not returns customer records with activity that does not match the specified calendar date and time.
is not between	is not between returns customer records with activity that is not between the specified calendar dates and times, not including the specified dates and times.
is not NULL	is not NULL returns customer records that have a value.
is NULL	is NULL returns customer records that do not have a value.
is on or after	is on or after returns customer records with activity that occurred on or after the specified calendar date and time, including the specified date and time.
is on or before	is on or before returns customer records with activity that occurred on or before the specified calendar date and time, including the specified date and time.

Decimal conditions

A Decimal data type represents amounts, percentages, and scores.

A Decimal data type accepts numeric values with a precision of 38 and a scale of 2 (default). Precision is the number of digits that may be in the decimal value. Scale is the number of digits that may be to the right of the decimal point.

Note

Amperity defaults precision and scale for the Decimal data type to 38 and 0: DECIMAL(38,2). The default value for scale may be configured in the feed for each data source.

The following conditions are available to all attributes with the Decimal data type:

Operator	Description
is	is returns customer records with values that match the specified amount or percentage.
is between	is between returns customer records with values that are between the specified amounts or percentages, not including the specified amounts or percentages.
is greater than	is greater than returns customer records with values that are greater than the specified amount or percentage, not including the specified amount or percentage.
is greater than or equal to	is greater than or equal to returns customer records with values that are greater than or equal to the specified amount or percentage, including the specified amount or percentage.
is in list	is in list returns customer records with values that match the amounts or percentages that are specified in the list.
is less than	is less than returns customer records with values that are less than the specified amount or percentage, not including the specified amount or percentage.
is less than or equal to	is less than or equal to returns customer records with values that are less than or equal to the specified amount or percentage, including the specified amount or percentage.
is not	is not returns customer records with values that do not match the specified amount or percentage.
is not between	is not between returns customer records with values that are not between the specified amounts or percentages, not including the specified amounts or percentages.
is not in list	is not in list returns customer records with values that do not match the amounts or percentages that are specified in the list.
is not NULL	is not NULL returns customer records that have a value.
is NULL	is NULL returns customer records that do not have a value.

Integer conditions

An Integer data type represents quantities, such as items ordered, frequency of purchase, number of orders, clicks, and page visits.

An Integer data type accepts numeric values with an implied scale of zero.

The following conditions are available to all attributes with the Integer data type:

Operator	Description
is	is returns customer records with values that match the specified quantity.
is between	is between returns customer records with values that are between the specified quantities, not including the specified quantity.
is greater than	is greater than returns customer records with values that are greater than the specified quantity, not including the specified quantity.
is greater than or equal to	is greater than or equal to returns customer records with values that are greater than or equal to the specified quantity, including the specified quantity.
is in list	is in list returns customer records with values that match the quantities that are specified in the list.
is less than	is less than returns customer records with values that are less than the specified quantity, not including the specified quantity.
is less than or equal to	is less than or equal to returns customer records with values that are less than or equal to the specified quantity, including the specified quantity.
is not	is not returns customer records with values that do not match the specified quantity.
is not between	is not between returns customer records with values that are not between the specified quantities, not including the specified quantity.
is not in list	is not in list returns customer records with values that do not match the quantities that are specified in the list.
is not NULL	is not NULL returns customer records that have a value.
is NULL	is NULL returns customer records that do not have a value.

String conditions

A String data type represents many things, such as identifiers, names (of people, places, and products), phone numbers, etc.

A String data type accepts A-Z, a-Z, underscores, and hyphens.

The following conditions are available to all attributes with the String data type:

Operator	Description
is	is returns customer records with values that match a string of characters.
is blank	is blank returns customer records with values that are blank.
is in list	is in list returns customer records with values that match strings of characters that are specified in a list.
is like	is like returns customer records with values that have a matching string of characters within the string of characters.
is not	is not returns customer records with values that do not match a string of characters.
is not blank	is not blank returns customer records with values that are not blank.
is not in list	is not in list returns customer records with values that do not match strings of characters that are specified in a list.
is not like	is not like returns customer records with values that do not have a matching string of characters within the string of characters.
is not NULL	is not NULL returns customer records that have a value.
is NULL	is NULL returns customer records that do not have a value.

Relative dates

A relative date is determined at the time a segment is run, where today is the day on which the segment is run. For example: yesterday, 30 days ago, 14 days ago, or 1 year ago. The list of relative date values includes a series of common ranges, but you may also type in a more specific range, such as 2 months ago or 5 days ago.

Relative date values

Value	Description
Tomorrow	Starts at 12:00:00 AM of the day after the current day. For example, if the current day is “Thursday 01 / 12 / 2023” then tomorrow is “Friday 01 / 13 / 2023”.
Today	Starts at 12:00:00 AM (or at the current time) on the current day and continues for 24 hours. For example, if the current day is “Thursday 01 / 12 / 2023” then today is “Thursday 01 / 12 / 2023”.
Yesterday	Starts at 12:00:00 AM of the day before the current day. For example, if the current day is “Thursday 01 / 12 / 2023” then yesterday is “Wednesday 01 / 11 / 2023”.
N days ago	Starts at 12:00:00 AM of the day N days before the current day. For example, if the current day is “Thursday 01 / 12 / 2023”, then: 7 days ago is “Thursday 01 / 05 / 2023” 14 days ago is “Thursday 12 / 29 / 2022” 30 days ago is “Tuesday 12 / 13 / 2022” 60 days ago is “Sunday 11 / 13 / 2022” 90 days ago is “Friday 10 / 14 / 2022”
1 month ago	Starts at 12:00:00 AM of the same day of the month that is 1 month before the current month. For example, if the current day is “Thursday 01 / 12 / 2023” then 1 month ago is “Monday 12 / 12 / 2022”.
1 year ago	Starts at 12:00:00 AM of same day of the year that is 1 year before the current year. For example, if the current day is “Thursday 01 / 12 / 2023” then 1 year ago is “Wednesday 01 / 12 / 2022”.

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 vs. OR works

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 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.

Attributes breakdown

The Breakdown page contains Segment insight charts for customer behaviors and customer attributes. These charts have a configurable date range and the displayed attributes charts are customizable. To customize the breakdown charts displayed on the Breakdown page, 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.

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.

How-tos

This section describes tasks related to building segments in Amperity:

• Access downstream campaigns

• Add attribute

• Browse tables and columns

• Add segment

• Comment on a query

• Compare segment insights

• Configure recommended segments

• Copy a segment ID

• Copy a SQL Query

• Delete a segment

• Discard segment

• Download segment

• Duplicate segment

• Edit segment from the Segments page

• Edit segment from Segment Editor

• Expand a graph

• Explore a segment copy

• Format a segment

• Open data explorer

• Organize segments

• Rename a segment

• Rerun a segment

• Search segments

• Select database

• Select multiple values

• Set default charts

• Show columns

• Switch to SQL segment

• Use relative dates

• View edit history

• View matching records from a table

• View a segment

• View SQL for segment statistics

Access downstream campaigns

You can access downstream campaigns from the Segments page.

To access a downstream campaign

1. From the Segments page, in the All segments section, in the Used in column, click the downstream campaign link.

The Edit Campaign page appears with the downstream campaign information.

Add attribute

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

Add attribute from table

You can add attributes from a table to a segment on the Segment Editor.

To add an attribute from a table to a segment

1. From the Segment Editor, click Add Attribute.

2. From the Source menu, either select a table source or search for the a table source from the search field.

3. From the Attribute menu, either select an attribute or search for an attribute in the search field.

4. From the Condition menu, select a condition.

5. From the value menu, either select a value or search for a value in the search field.

6. Add another attribute or section.

7. When done, click Save As.

The data appears on the Segments page.

Add attribute from query

You can add attributes from a query to a segment on the Segment Editor.

To add an attribute from a query to a segment

1. From the Segment Editor, click Add Attribute.

2. From the Source menu, either select a query source or search for a query source in the search field.

3. From the Attribute menu, either select an attribute or search for an attribute in the search field.

4. From the Condition menu, select a condition.

5. From the value menu, either select a value or search for a value in the search field.

6. Add another attribute or section.

7. When done, click Save As.

The data appears on the Segments page.

Add transactional behaviors

You can add transaction behaviors from the Segment Editor.

To add transactional behavior attributes to a segment

1. From the Segment Editor, click Add criteria.

2. Select one an attribute, from the Transactional Activity menu.

3. Select a source from the Sources menu.

   Tip

   You can also use the Search field to find a source.

4. In the menu, select a segment attribute.

5. In the Operators menu, select an condition.

   Note

   You can delete an attribute by clicking on the ‘x’ to the right of the criteria.

6. Enter information into the required fields.

7. Click Add filter.

8. From the Filters window, select the appropriate conditions and values.

9. Click Save As. The filters appear on the Segment Editor window beneath the associated attributes.

10. When done adding criteria and sections, click Save As to update the segment.

Add condition

You can add conditions to an attribute in a segment on the Segment Editor.

To add a condition to an attribute in a segment

1. From the Segment Editor, click Add Attribute.

2. From the Source menu, either select a source or search for a source in the search field.

3. From the Attribute menu, either select an attribute or search for an attribute in the search field.

4. From the Condition menu, select a condition.

5. From the value menu, either select a value or search for a value in the search field.

6. Add another attribute or section.

7. When done, click Save As.

The data appears on the Segments page.

Add section

You can add sections to a segment on the Segment Editor.

To add a section to a segment

1. From the Segment Editor, click Add Section.

2. Click Add Attribute.

3. From the Source menu, either select a source or search for a source in the search field.

4. From the Attribute menu, either select an attribute or search for an attribute in the search field.

5. From the Condition menu, select a condition.

6. From the value menu, either select a value or search for a value in the search field.

7. Add another attribute or section.

8. When done, click Save As.

The data appears on the Segments page.

Add a query output to a segment

You can add a query output to a segment from the Segment Editor.

To add a query output to a segment

1. From the Segment Editor window, click Add Attribute.

2. From the Source menu, either select a table source or search for a table source in the search field.

3. From the Attribute menu, either select an attribute or search for an attribute in the search field.

4. From the Condition menu, select a condition.

5. From the value menu, either select a value or search for a value in the search field.

6. Click Add List.

7. From the Condition list, select Is a member of….

8. From the Customer Lists list, in the Queries section, select a query output.

   Note

   To delete a segment associated with a query output, you will need to first delete the query output before being able to delete the segment.

9. Click Save As.

The data appears on the Segments page.

Note

In order for a query output to appear on the Segment Editor, you will need to add the Amperity ID field to the query.

Add an uploaded file to a segment

You can add an uploaded file to a segment from the Segment Editor.

To add an uploaded file to a segment

1. From the Segment Editor window, click Add Attribute.

2. From the Source menu, either select a table source or search for a table source in the search field.

3. From the Attribute menu, either select an attribute or search for an attribute in the search field.

4. From the Condition menu, select a condition.

5. From the value menu, either select a value or search for a value in the search field.

6. Click Add List.

7. From the Condition list, select Is a member of….

8. From the Customer Lists list, in the File Uploads section, select an uploaded file output.

   Note

   To delete a segment associated with a query output, you will need to first delete the uploaded file output before being able to delete the segment.

9. Click Save As.

The data appears on the Segments page.

View uploaded files

You can view a list of uploaded files on the Segment Editor.

To view uploaded files

1. From the Segment Editor window, click Add List.

2. From the Condition list, select Is a member of….

3. From the Customer Lists list, in the File Uploads section, view a list of uploaded files.

   Note

   When you upload a file to Amperity, the system will write a table from the data contained in that file. The table is then layered on top of a database at the queries (storage-service) layer.

   Amperity does not enforce a time constraint on how long uploaded files can remain in the database. To remove an uploaded file from that database, please contact your Amperity Customer Support representative.

Add segment

You can add a segment on the Segments page.

To add a segment

1. From the Segments page, either click Create Segment or select a segment, click Actions, and then, in the menu, click Edit segment.

2. On the Segment Editor window, click Add Attribute.

3. From the Source menu, either select a source or search for a source in the search field.

4. From the Attribute menu, either select an attribute or search for an attribute in the search field.

5. From the Condition menu, select a condition.

6. From the value menu, either select a value or search for a value in the search field.

7. Add another attribute or section.

8. When done, click Save As.

The segment data appears on the Segments page.

Browse tables and columns

The Segment Editor provides access to all tables in all databases that have been made available for use with segments. These are available from a list in the segment editor, sorted by table, and then within each table sorted by field. Use this list as a quick reference for tables, columns, and data types as you are building segments.

To browse tables and columns

1. From the Segments page, open a segment. This opens the Segment Editor.

2. Under Database, select a database from the drop-down menu. The list of tables is updated to show the tables in that database.

3. Under Table, expand the name of a table. Details include the number of records in the table, a list of columns, and for each column its data type.

Change insight date range

You can change the insight details date range on the Segments page.

To change the insight details date range

1. From the Segments page, in the More Insights section, click the date range field.

2. Select a date range from the menu.

   The updated insights data appears on the Segments page.

Comment on a query

You can add comments to the query in a segment.

To add comments to a query

1. From the Segment Editor, click View SQL

2. On the Visual SQL window, click Convert to SQL Segment.

3. On the SQL Segment Editor, click Comment.

4. Enter your comments.

5. Click Activate.

   The segment data appears on the Segments page.

Compare segment insights

You can compare segment insights by the following:

• Purchasers percentage

• Revenue percentage

• Revenue/Purchaser

To add compare segments insights

1. From the Segments page, from the More Insights section, click the down arrow in the Compare by: field.

2. Select one of the following options from the list:

   • % of Purchasers

   • % of Revenue

   • Revenue/Purchaser

   The updated insights data appears on the Segments page.

Configure recommended segments

You can configure recommended segments on the Segment page.

1. From the Segments page, click Configure.

2. In the table section, select a segment.

3. Select an icon.

4. Click Save.

   The recommended segment(s) appear on the Segments page.

Copy a segment ID

You can copy a segment ID on the Segments page.

1. From the Segments page, open the menu for a segment.

2. In the menu, click Copy ID.

3. Paste the segment ID in the appropriate location.

Copy a SQL Query

You can copy a SQL query from the Segment Editor.

1. From the Segment Editor, click View SQL

2. On the View SQL window, click Convert to SQL Segment.

3. On the SQL Segment Editor, click Copy as SQL Query.

4. On the Copy as SQL Query window, click Copy as SQL Query.

5. On the SQL Query Editor page, make your changes.

6. When done with creating the query, click Activate.

   The new query appears on the Queries page.

   Tip

   To include customer matches, you can select the Include “Customer Matches” columns option.

Customize insights charts

You can customize insights charts on the Segments page.

To customize insights charts

1. From the Segment page, in the More Insights section, click Customize.

2. On the Customize Insights Charts window, you can either select up to 6 customer attributes or select up to 6 behavioral attributes.

3. Once done updating the insights charts, click Apply.

   The default charts are available to all users of the Segments page.

   Note

   To reset the insight charts to the default charts, click Reset at the bottom of the Customize Insights Charts window.

Delete a segment

You can delete a segment from the Segments page.

To delete a segment

1. From the Segments page, open the menu for a segment.

2. In the menu, click Delete.

3. On the Delete Segment window, click Confirm.

   The segment no longer appears on the Segments page.

Bulk delete segments

You can delete multiple segments from the Segments page.

To delete multiple segments

1. From the Segments page, select multiple segments.

2. On the bottom of the Segments page, click Delete.

3. On the Bulk Delete window, click Delete <#> Items.

   The segments no longer appear on the Segments page.

Discard segment

Use the Discard option to remove a segment from Amperity. This should be done carefully. Verify that both upstream and downstream processes no longer depend on this segment prior to discarding it.

To discard a segment

1. From the Segments page, open the menu for a segment, and then select Discard. The Discard Segment dialog box opens.

2. Click Confirm.

Download segment

You can download segment results as a CSV file. The CSV format is supported by many applications, which makes the format a great way to test the potential of orchestrating segments for downstream applications and workflows.

Note

You cannot download the results of any segment that returns an error.

To download a segment as a CSV file

1. From the Segments page, open the menu for a segment, and then select View. This opens the segment editor.

2. Click the Customers page.

3. Click Download.

4. A CSV file with a filename that is identical to the segment name is downloaded to your local machine.

Duplicate segment

You can duplicate a segment from the Segments page.

To duplicate a segment

1. From the Segments page, open the menu for a segment.

2. Click Duplicate.

3. On the Duplicate Segment window, click Confirm.

4. On the Segment Editor, make your changes, and then click Save As.

   The duplicated segment appears on the Segments page.

Edit segment from the Segments page

You can edit a segment from the Segments page.

To edit a segment

1. From the Segments page, open the menu for a segment.

2. Click Edit.

3. On the Segment Editor, make your changes, and then click Save.

   The updated segment data appears on the Segments page.

Edit segment from Segment Editor

You can edit a segment from the Segment Editor.

To edit a segment from the Segment Editor

1. From the Segment Editor, click Actions (upper-right corner).

2. Click Edit.

3. Make your changes and then click Save.

   The updated segment data appears on the Segments page.

Expand a graph

You can expand graphs on the Segments page.

To expand a graph

1. From the Segments page, open the menu for a graph.

2. Click Expand.

   The graph opens up in a window with more details.

Explore a segment copy

You can explore a copy of a saved segment on the Summary page.

To explore a copy of a saved segment

1. From the Summary page, click Explore a Copy.

2. From the Segments Editor, you can do one of the following:

   Explore the saved segment attribute details

   Add new attributes, conditions, and filters to the segment copy

3. When done, either click Save As to copy the saved segment, or click View to view the segment insights on the Summary page, or click Cancel.

Format a segment

You can format a segment from the Segments page.

1. From the Segments page, open the menu for a segment.

2. Click Edit.

3. On the Segment Editor, make your changes, and then click Save.

The updated segment data appears on the Segments page.

Open data explorer

You can open the data explorer from the Segments page.

To open the data explorer

1. From the Segment Editor page, in the Details section, click Open Data Explorer.

2. The Data Explorer appears with the following customer details:

   The Data Explorer page appears with information about standard tables and source and custom tables, and C360 database details.

Tip

You can use the search field at the top of the screen to search for tables and fields.

Organize segments

A folder helps you organize the list of segments in the Segments tab. Up to three levels may be added.

You can organize the segments shown in the Segments page:

• Add a folder

• Add a subfolder

• Move a segment to another folder

• Save segment to a folder

Add folders

Folders may be expanded (or collapsed) to view (and hide) the list of segments and subfolders contained within.

To add a folder

1. From the Segments page click Create, and then select Add Folder. This opens the Create Folder dialog box.

2. Enter the name for the folder.

3. Click Create.

Add subfolders

Use the Create folder option in the menu to add up to three levels of subfolders. All folder names must be unique.

To add a subfolder

1. From the Segments page, open the menu for a folder, and then select Create folder. This opens the Create Folder window.

2. Enter the name for the folder.

3. Click Save.

Move segment

Use the Move option to move around and organize the list of folders and segments. Folders may be expanded (or collapsed) to view (and hide) the list of segments and subfolders contained within.

To move a segment

1. From the Segments page, open the menu for a segment, and then select Move. This opens the Move Segment dialog box.

2. Select the name of an existing folder to which a segment will be moved, and then click Move.

Hint

If the folder to which a segment will be moved is not present in the list of folders, you can add it directly from the Move Segment dialog box. Click the + New folder link, type a name for the folder, and then select it.

Save segment to a folder

You can save a segment into a folder from the Segment Editor.

To save a segment to a folder from the Segment Editor

1. From the Segment Editor, click Save as.

2. From the Save as a new segment window, enter the name in the Name field.

3. In the Location section, select the folder or subfolder.

4. Click Save.

The segment appears in the folder on the Segments page.

Bulk move segments

You can move multiple segments to a folder from the Segments page.

To move multiple segments to a folder

1. From the Segments page, select multiple segments.

2. On the bottom of the Segments page, click Move.

3. On the Bulk Move window, select a folder.

4. Click Move.

   The segments appear in the folder on the Segments page.

Rename a segment

You can rename a segment from the Segments page.

To rename a segment

1. From the Segments page, open the menu for a segment.

2. Click Rename.

3. On the Rename segment window, enter a name.

4. Click Save.

   The updated segment name appears on the Segments page.

Rerun a segment

You can rerun a segment from the Segments page.

To rerun a segment

1. From the Segments page, on the Customers page, click Rerun.

2. The system reruns the segment the customer data on the Customers page is updated.

Search segments

You can search for segments on the Segments page.

To search for a segment

1. From the Segments page, open a segment.

2. On the top of the Segments page, enter the name of the segment into the search field.

   The segment appears in a list on the Segments page.

   Tip

   Select the Also search segment content option to search segment content.

Select database

You can build a segment against any database that is visible from the Customer 360 page.

To select a database

1. From the Segments page, click Create, and then select Visual Segment. This opens the Segment Editor.

2. Under Database, select a database. The Customer 360 database is selected by default.

3. Build your segment against the list of tables that are available in that database.

Select multiple values

You can select multiple values from the Segment Editor.

To add attribute groups to a segment

1. From the Segment Editor, click Add criteria.

2. Select a table or search for an attribute in the search field.

3. Select a condition.

4. In the field, search for or select values.

   Tip

   You can search for a value and then easily select all options in the list of values that appears by selecting the Select all checkbox.

5. Click Save.

6. When done adding criteria and sections, click Save to update the segment.

Set default charts

You can set and default charts from the Segment Editor.

To set default charts

1. From the Segment Editor, click Actions.

2. In the list that appears, click Set default charts.

3. On the Set Default Insights Charts window, you can either select up to 6 customer attributes or select up to 6 behavioral attributes.

4. Once done updating the default charts, click Save.

   The default charts are available to all users of the Segments page.

Show columns

You can view columns that are in the segment results from the Customers page in the segment viewer. This can be configured to show all columns from all tables or only columns from a specific table.

To show columns

1. From the Segments page, open the menu for a segment, and then select View. This opens the segment editor.

2. Click the Customers page.

3. Expand the Show [x] columns from [table] link.

4. Use the Show all columns and Show only the columns I choose options to configure which columns are shown.

5. Click Refresh to update the segment results to show the configured set of columns.

Switch to SQL segment

You can switch a visual segment to a SQL segment.

To switch to a SQL segment

1. From the Segment Editor, open a segment.

2. In the Segment Editor, in the top right, click View SQL.

3. Click Convert to SQL Segment.

Use relative dates

A relative date is determined at the time a segment is run, where today is the day on which the segment is run. For example: yesterday, 30 days ago, 14 days ago, or 1 year ago.

#.From the Segment Editor, click Add attributes, and then choose an attribute with a date or datetime value. #. Select the Use relative dates option, and then specify the relative date (or dates) that match the condition you selected. For example: “30 days ago”. #. Click Refresh to validate the segment. #. Click Save As.

Tip

To build a segment using relative dates, Amperity turns datetime fields into dates.

View edit history

You can view information on the edit history for a segment from the Segments page.

To view the edit history for a segment

1. From the Segments page, open the menu for a segment.

2. Click Edit History.

The Segment history window appears with informations about who edited the segment, the date(s) when the segment was edited, and the description(s) of what was edited.

View matching records from a table

You can view matching records from a table from the Customers page on the Segments page.

To view matching records from a table

1. From the Segments page, on the Customers page, expand the Show [x] columns from [table] link.

2. Click in the Show matching records from: field.

3. In the list that appears, select a table.

The updated customer data appears on the Segments page.

View a segment

You can view a segment on the Segments page.

To view a segment

1. From the Segments page, click on a segment.

2. The segment appears displaying a summary page with insight details.

   Tip

   You can find and view the draft segments at the bottom of the Segments page.

View SQL for segment statistics

You can view the SQL for segment statistics on the Segments page in the Summary and Breakdown tabs.

To view the SQL for segment statistics on the Segments page

1. From the Segments page, on the either the Summary tab or the Breakdown tab, click the options icon on a segment data card.

2. Click View SQL.

The View SQL window appears with the SQL for the segment statistics.