Structured Data

Extract entities and targeted data from your conversations

Structured data extracts specific, customizable data points from conversations. This feature includes two main components:

• Entity extraction: Automatically identifies and extracts specific information from conversations.
• Question extraction (Targeted Structured Data): Answers predefined questions based on conversation content.

Both entity and question extraction come with industry-specific templates that can be customized to fit your unique use cases.

Structured data’s flexible nature enables it to solve numerous challenges, including:

• Automating data collection for analytics and reporting
• Facilitating compliance monitoring and quality assurance
• Populating CRMs and other business tools efficiently
• Supporting data-driven decision-making and process improvement

How it works

Here’s an example conversation to demonstrate how Structured Data works:

Agent: Hello, thank you for contacting XYZ Insurance. How can I assist you today?
Customer: Hi, I want to check the status of my payout for my claim.
Agent: Sure, can you please provide me with the claim number?
Customer: It’s H123456789.
Agent: Thank you. Could you also provide the last 4 digits of your account number?
Customer: 6789
Agent: Let me check the details for you. One moment, please.
Agent: I see that your claim was approved on June 10, 2024, for $5000. The payout has been processed.
Customer: Great! When will I receive the money?
Agent: The payout will be credited to your account within 3-5 business days.
Customer: Perfect, thank you so much for your help.
Agent: You’re welcome! Is there anything else I can assist you with?
Customer: No, that’s all. Have a nice day.
Agent: You too. Goodbye!

AI Summary analyzes this conversation and extracts structured data in two ways:

Entity

Entity Extraction automatically identifies and extracts specific information from conversations. Extracted entities can include claim numbers, account details, dates, monetary amounts, and more.

For the example conversation above, the extracted entities would look like this:

[
    {
      "name": "Claim Number",
      "value": "H123456789"
    },
    {
      "name": "Account Number Last 4",
      "value": "5678"
    },
    {
      "name": "Approval Date",
      "value": "2024-06-10"
    },
    {
      "name": "Payout Amount",
      "value": 5000
    }
]

Question

Targeted Structured Data (Questions) provides answers to predefined queries based on conversation content. You can customize these questions to address specific aspects of customer interactions, compliance requirements, or other relevant factors.

For the example conversation above, predefined questions and their answers would look like this:

[
    {
      "name": "Customer Satisfied",
      "answer": "Yes"
    },
    {
      "Name": "Payout Information Provided",
      "answer": "Yes"
    },
    {
      "name": "Verification Completed",
      "answer": "Yes"
    }
]

Structured Data Dashboard

Use the Structured Data dashboard to configure which entities or questions you want to extract.

Once configured, ASAPP will return the extracted structured data.

The Structured Data dashboard enables you to:

• Add new entities: Define fields to extract from conversations, such as order numbers, dates, amounts, or other relevant data points.
• Add new questions: Create targeted questions to answer based on conversation content. Tailor these questions to your specific use cases, including compliance checks, behavioral insights, or downstream workflows.
• Modify or delete existing entities and questions: Rename, change types, or update parameters for existing entities or questions to better suit your requirements. Remove any entities or questions that are no longer needed.
• Control visibility and lifecycle: Enable or disable fields based on team, workflow, or environment.
• Preview changes: Preview and validate extraction behavior before publishing.

Before you begin

Before configuring Structured Data, ensure you have:

• Access to the AI Summary dashboard with necessary permissions to manage Structured Data settings.

Configure Structured Data

Configure Structured Data to extract specific entities and answer questions most relevant to your business needs.

Follow these steps:

1. Access the Structured Data Dashboard from your AI Summary dashboard.
2. Navigate to the “Structured Data” section.
3. Select Create Data Fields and click Create Entity or Create Question.
4. Fill in the required details: name, description, category, segment tag, and examples (for entities).
5. Click Create to save the new entity or question.

Once you’ve configured your entities and questions, they’ll appear in the Structured Data Interface where you can edit, delete, or manage their visibility as needed.

View Extracted Structured Data

Successfully created Structured Data returns extracted data within 24 hours.

View extracted structured data in a dashboard under the “Historical Data” section within the AI Console interface. You can also download the structured data as a report in either CSV or PDF format from this dashboard.

The structured data represents both the entities and answered questions you’ve configured.

You can export structured data to your data warehouse via S3 bucket. Contact your ASAPP account team to enable this feature.

Customization

Structured Data questions and entities are fully customizable to meet your business needs.

We provide industry-specific questions and entities to get you started. Work with your ASAPP account team to determine whether our out-of-the-box configurations meet your needs or if custom structured data is required.

Use our APIs to self-serve custom structured data fields.