Segments and Customization

Learn how to customize the data extracted with Structured Data.

Each business has unique needs and requirements for the type of data they want to extract from their conversations.

We offer out-of-the-box configuration for common use cases but also offer two sets of APIs for you to customize the structured data yourself:

• Create custom structured data fields to expand the types of data you can extract.
• Create segments to customize which sets of structured data the system extracts for a defined type of conversation.

Before you Begin

Before you start integrating to Custom Structured Data Fields and Segments, you need to:

• Get your API Key Id and Secret
• Ensure your API key has been configured to access AI Summary Configuration APIs. Reach out to your ASAPP team if you are unsure.

Custom Structured Data Fields

Each structured data you extract is defined by a structured-data-field. ASAPP sets up an initial set of structured data fields for you, but you can also query and create custom structured data fields yourself.

To create a custom structured data field, you need to create a new structured-data-field object with the following fields:

• id: Your unique identifier for the structured data field. Must begin with q_ or e_.
• name: The name of the structured data field.
• categoryId: The category of the structured data field. Must be either OUTCOME or CUSTOM.
• type: The type of the structured data field. Must be either QUESTION or ENTITY.
• question: The question that the system will answer using the context of the conversation.
• active: Whether the structured data field is active.

curl --request POST \
  --url https://api.sandbox.asapp.com/configuration/v1/structured-data-fields \
  --header 'Content-Type: application/json' \
  --header 'asapp-api-id: <api-key>' \
  --header 'asapp-api-secret: <api-key>' \
  --data '{
  "id": "q_promotion_was_offered",
  "name": "Promotion was offered",
  "categoryId": "OUTCOME",
  "type": "QUESTION",
  "question": {
    "question": "Did the agent offer the correct promotion?"
  },
  "active": true
}'

A successfully created structured data field returns a 200 status code and the newly created structured-data-field object in the response body.

{
  "id": "q_promotion_was_offered",
  "name": "Promotion was offered",
  "categoryId": "OUTCOME",
  "type": "QUESTION",
  "question": {
    "question": "Did the agent offer the correct promotion?"
  },
  "active": true
}

The system will not extract an inactive structured data field from conversations.

You can then use the structured data field id to create a segment.

Segments

Segments configure which sets of structured data fields the system extracts for a defined type of conversation. Segments are defined by two parts:

• A query that matches against the conversation metadata and intent.
• A list of structured data field ids that the segment includes.

When you generate structured data for a conversation, the system follows these steps:

1. Checks the conversation against the queries of all segments
2. For each matching query:
   • Extracts the structured data fields that the segment defines
3. If multiple segments match:
   • Combines and extracts all structured data fields from all matching segments

By default, there is a GLOBAL segment that represents the initially configured structured data fields with a query that matches TRUE on any conversation.

Most companies will want to create custom segments to extract structured data fields for specific types of conversations, such as a support call involving a specific product or service, or types of sales calls.

Create a new segment

To create a new segment, you need to create a new segment object with the following fields:

• id: Your unique identifier for the segment.
• name: The name of the segment.
• query: The query that defines which conversations are included in the segment.
• structuredDataFieldIds: The list of structured data field ids that the segment includes.

curl --request POST \
  --url https://api.sandbox.asapp.com/configuration/v1/segments \
  --header 'Content-Type: application/json' \
  --header 'asapp-api-id: <api-key>' \
  --header 'asapp-api-secret: <api-key>' \
  --data '{
  "id": "USER_SUPPORT",
  "name": "Support",
  "query": {
    "type": "raw",
    "raw": "TRUE"
  },
  "structuredDataFieldIds": [
    "q_promotion_was_offered",
    "e_promotion_details"
  ]
}'

A successfully created segment returns a 200 status code and the newly created segment object in the response body.

{
  "id": "USER_SUPPORT",
  "name": "Support",
  "query": {
    "type": "raw",
    "raw": "TRUE"
  },
  "structuredDataFieldIds": [
    "q_promotion_was_offered",
    "e_promotion_details"
  ]
}

Query

The segment’s query defines rules for when the system should apply a segment to a conversation. We currently only support a query type of raw that uses a SQL-like syntax with a focused set of operators for clear and precise matching.

The query language supports these key elements:

Logical Operators

• AND, OR, NOT - Combine conditions
• Parentheses () for grouping and precedence

Field Comparisons

• Equality: field = 'value'
• List membership: field IN ['value1', 'value2']

Available Fields

The data you can query against is the conversation metadata that you upload as part of metadata ingestion.

Specifically, you can query against the following fields:

Conversation Metadata

Field	Description
lob_id	Line of business identifier
lob_name	Line of business name
group_id	Group identifier
group_name	Group name
agent_routing_code	Agent’s routing attribute
campaign	Activities related to the issue
device_type	Client’s device type (TABLET, PHONE, DESKTOP, WATCH, OTHER)
platform	Client’s platform type (SMS, WEB, IOS, ANDROID, APP, LOCAL, VOICE, VOICE_IOS, VOICE_ANDROID, VOICE_ECHO, VOICE_HOMEPOD, VOICE_GGLHOME, VOICE_WEB, APPLEBIZ, GOOGLEBIZ, GBM, WAB)
company_segment	Company’s segment(s) that the issue belongs to
company_subdivision	Company’s subdivision that the issue belongs to
business_rule	Business rule to use
entry_type	Way the issue started and created in the system
operating_system	Operating system used to enter the issue (MAC_OS, LINUX, WINDOWS, ANDROID, IOS, OTHER)
browser_type	Browser type used
browser_version	Browser version used

Conversation Intent

Field	Description
intent_code	Intent identifier
intent_name	Intent name

Query Examples

Here are some examples of how queries can be constructed for different types of conversations.

Note that the field values used in these examples are arbitrary and for illustration purposes only. You will need to construct queries using your actual metadata fields and values based on your business needs.

Match conversations for mobile products AND the iOS platform

group_id IN ['mobile_support', 'mobile_tech'] AND platform = 'ios'

Match conversations for up-sell and cross-sell opportunities

intent_code IN ['UPGRADE_INQUIRY', 'ADDITIONAL_SERVICE', 'PREMIUM_FEATURES'] 
AND company_subdivision = 'inside_sales'

Match high-priority complaints

intent_code = 'COMPLAINT' AND campaign = 'holiday_season' AND business_rule = 'high_priority'

Match billing conversations for wireless and broadband services

intent_code = 'BILLING' AND lob_id IN ['wireless_service', 'broadband_service']

Global Segment

The GLOBAL segment is a special segment that matches all conversations. The system automatically creates it when you first configure your structured data fields.

You can update the GLOBAL segment to include new structured data fields or modify the query to change the criteria for matching conversations.

We recommend that once you start creating custom segments, you update the GLOBAL segment to remove the structured data fields and rely on the custom segments to extract structured data.