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What is Post Call Analysis?

Post Call Analysis helps you understand what happened in conversations between your AI assistant and users. Think of it like a smart report card that automatically grades and categorizes each conversation. For example, you can:

• Track if users were satisfied with the conversation
• Extract structured data from conversations
• Categorize conversations into specific groups
• Summarize the conversation between the AI Agent and the user
• Measure how well your AI assistant is performing

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Types of Post Call Analysis Fields

You can collect different types of information using four field types:

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1. Text Fields 📝

• What they are : Fields where you can write any text
• Best for : Storing detailed notes, comments, or feedback, summarizing the conversation
• Example : “What did the customer say about our service?“

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2. Yes/No Fields ✓/✗

• What they are : Fields with only two possible answers (Yes/No, True/False)
• Best for : Simple questions with clear answers, extracting boolean values
• Example : “Did the customer’s problem get solved?“

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3. Choice Fields 📋

• What they are : Fields with a list of options to choose from
• Best for : Categorizing conversations into specific groups
• Example : “Which product did the customer ask about?“

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4. Number Fields 🔢

• What they are : Fields that only accept numbers
• Best for : Ratings, scores, or counting things, extracting numerical values
• Example : “Rate the conversation from 1 to 5”

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How to Set Up Post Call Analysis Fields

Let’s walk through how to set up each type of field:

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Step 1: Open the Analysis Settings

1. Go to your dashboard
2. Click on “Post Call Analysis”
3. Click the “Add Field” button

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Step 2: Choose Your Field Type

Pick the type of field that matches what you want to track:

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Text Field Example

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Yes/No Field Example

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Choice Field Example

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Number Field Example

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Step 3: Configure Your Field

For each field:

1. Give it a clear name (like “customer_satisfaction”)
2. Write a clear description that acts like a prompt
   • Be specific about what you want to extract
   • Use clear instructions
   • Include format requirements if any
   • Add examples if helpful

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Writing Good Descriptions

Your description tells the AI what to look for and how to format the response. Here are examples for each field type:

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Text Field Description Examples

✅ Good: “Summarize the main complaint or issue the customer reported. Include the specific product/service mentioned and any error messages if applicable.” ❌ Bad: “Get customer complaint”
✅ Good: “List the specific next steps agreed with the customer. Format as bullet points, starting with action verbs.” ❌ Bad: “What are the next steps”

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Yes/No Field Description Examples

✅ Good: “Did the customer explicitly express satisfaction with the resolution? Answer ‘Yes’ only if they clearly stated they were satisfied.” ❌ Bad: “Customer satisfied?”
✅ Good: “Was a refund requested during the conversation? Check for any mention of ‘refund’, ‘money back’, or similar phrases.” ❌ Bad: “Refund needed”

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Choice Field Description Examples

✅ Good: “Identify the primary reason for the call. Choose the category that best matches the customer’s first reported issue, not subsequent topics discussed.” ❌ Bad: “What did they call about”
✅ Good: “Determine the customer’s subscription tier mentioned during the call. If multiple tiers are discussed, select the one they currently have.” ❌ Bad: “Customer tier”

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Number Field Description Examples

✅ Good: “Extract the total amount the customer is willing to spend, mentioned in dollars. If a range is given, use the higher amount.” ❌ Bad: “How much will they spend”
✅ Good: “Rate the customer’s frustration level from 1-5 based on their tone and words used. 1=Very calm, 3=Moderate frustration, 5=Extremely frustrated.” ❌ Bad: “Customer frustration level”

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Real-World Example: Employee Satisfaction Survey

Let’s walk through how to set up Post Call Analysis fields for an employee satisfaction survey. We’ll create fields to extract answers for each survey question.

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Survey Questions

1. “How would you rate your overall job satisfaction on a scale of 1 to 5?”
2. “Would you recommend our company as a good place to work?”
3. “Which department do you currently work in?”
4. “What specific factors contribute to your satisfaction or dissatisfaction?”

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Step-by-Step Field Setup

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Step 1: Create Number Field for Satisfaction Rating

1. Click “Add Field”
2. Select “Number” as the field type
3. Configure the field:
   • Name : satisfaction_rating
   • Description : “Extract the employee’s job satisfaction rating on a scale of 1 to 5, where 1 is very dissatisfied and 5 is very satisfied. Only accept whole numbers between 1-5.”
4. Click “Save”

Expected Result: A number between 1-5 (Example: “4”)

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Step 2: Add Yes/No Field for Company Recommendation

1. Click “Add Field”
2. Select “Yes/No” as the field type
3. Configure the field:
   • Name : would_recommend_company
   • Description : “Determine if the employee would recommend the company as a workplace. Look for explicit statements of willingness to recommend. Answer ‘Yes’ only if they clearly indicate they would recommend.”
4. Click “Save”

Expected Result: “Yes” or “No”

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Step 3: Set Up Choice Field for Department

1. Click “Add Field”
2. Select “Choice” as the field type
3. Configure the field:
   • Name : employee_department
   • Description : “Identify which department the employee currently works in. Select from the available options. If multiple departments are mentioned, choose their current department.”
   • Add Choices :
     • Type “Engineering” and click Add
     • Type “Finance” and click Add
     • Type “Operations” and click Add
     • Type “Product Management” and click Add
4. Click “Save”

Expected Result: One of the predefined departments (Example: “Product Management”)

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Step 4: Create Text Field for Satisfaction Factors

1. Click “Add Field”
2. Select “Text” as the field type
3. Configure the field:
   • Name : satisfaction_factors_feedback
   • Description : “Extract and summarize the specific factors affecting the employee’s job satisfaction or dissatisfaction. Include:
     • Mentioned positive factors
     • Any areas of concern Format as a clear paragraph with specific examples mentioned.”
4. Click “Save”

Expected Result: A detailed paragraph (Example: “The employee expressed high job satisfaction, highlighting the interactive work environment and feeling valued. They mentioned no current factors contributing to dissatisfaction.”)