You’re an AI specialist responsible for precisely structuring insurance call transcripts into uniform JSON outputs with clearly defined tags and metadata. **user_prompt:** Transform this insurance conversation transcript into structured JSON format. Your tasks are to:
1. Identify Speakers: Properly tag &quot;Agent&quot;, &quot;Supervisor&quot; and &quot;Client.&quot;
2. Correct Grammar &amp; Clarity: Fix all grammatical errors while preserving meaning.
3. Structure the Conversation: Organize the dialogue logically.
4. Tag Call Completion: {0: &quot;Incomplete&quot;, 1: &quot;Complete&quot;} (Incomplete if the call was cut off, unanswered, or not fully concluded).
5. Extract Key Insights:
   - Client Age: {1: &quot;known&quot;, 0: &quot;unknown&quot;} integer if known otherwise 0
   - Identify Client Gender: {0: &quot;Male&quot;, 1: &quot;Female&quot;, 2: &quot;Unknown&quot;}
   - Call Outcome: {0: &quot;Not interested&quot;, 1: &quot;Interested&quot;, 2: &quot;Needs Follow-up&quot;, 3: &quot;Hung Up&quot;, 4: &quot;Not Eligible&quot;}
   - Client Insurance Status&quot;: {0: &quot;Not disclosed&quot;, 1: &quot;Has insurance&quot;, 2: &quot;Does not have insurance&quot;}
   - Client Objections &amp; Agent’s Responses
   - Decision Maker Confirmation: {0: &quot;No&quot;, 1: &quot;Yes&quot;, 2: &quot;unknown&quot;}
   - Client Sentiment: 0-9  (scale defined below)
   - Follow Up: {0: &quot;Not required&quot;, 1: &quot;Required&quot;}
   - Agent Performance: 0-9 (scale defined below)
   - Agent Persuasiveness: 0-4 (scale defined below)
   - Transfer Success: {0: &quot;Not Transferred&quot;, 1: &quot;Transferred&quot;}
   - Call Drop Reason: {0: &quot;Client Disengaged&quot;, 1: &quot;Technical Issue&quot;, 2: &quot;Agent Ended&quot;, 3: &quot;Client Hung Up&quot;, 4: &quot;Unknown&quot;}
   - Follow-up Type Required: {0: &quot;Not required&quot;, 1: &quot;Call&quot;, 2: &quot;Email&quot;, 3: &quot;In-person meeting&quot;}
   - Permission Confirmation: {0: &quot;No&quot;, 1: &quot;Yes&quot;, 2: &quot;Not Required&quot;} (detect if the client agreed to proceed with the call)
   - Do Not Call (DNC) Indicators: {0: &quot;No&quot;, 1: &quot;Yes&quot;} (if the client requests not to be contacted again)
   - Misrepresentation Risk: {0: &quot;No&quot;, 1: &quot;Yes&quot;} (flag if the agent made misleading statements)

Client Sentiment Scale (0-9) = {
    0: &quot;Extremely Negative&quot;,  # The client is angry, frustrated, or hostile. Very tense conversation.
    1: &quot;Highly Negative&quot;,  # The client is annoyed, upset, or dismissive, but not outright aggressive.
    2: &quot;Negative&quot;,  # The client is disinterested and quickly cuts off the agent.
    3: &quot;Somewhat Negative&quot;,  # The client is uninterested but polite.
    4: &quot;Slightly Negative&quot;,  # The client declines but listens briefly before rejecting the offer.
    5: &quot;Neutral&quot;,  # The client neither expresses strong rejection nor interest.
    6: &quot;Slightly Positive&quot;,  # The client engages in conversation but is hesitant.
    7: &quot;Somewhat Positive&quot;,  # The client shows genuine interest but has some reservations.
    8: &quot;Positive&quot;,  # The client is interested and may want to proceed but needs more details.
    9: &quot;Highly Positive&quot;  # The client is very engaged, excited, or ready to proceed.
}

Agent Performance Scale (0-9)= {
    0: &quot;Extremely Poor&quot;,  # Agent is unprofessional, rude, or misleading. May have upset the client.
    1: &quot;Very Poor&quot;,  # Agent is struggling to engage, lacks confidence, or is making mistakes.
    2: &quot;Poor&quot;,  # Agent fails to handle objections or provide clear information.
    3: &quot;Below Average&quot;,  # Agent is trying but is ineffective in guiding the conversation.
    4: &quot;Slightly Below Average&quot;,  # Agent communicates but does not engage well.
    5: &quot;Average&quot;,  # Agent follows the script but lacks enthusiasm or adaptability.
    6: &quot;Above Average&quot;,  # Agent engages well but could improve in persuasion or handling objections.
    7: &quot;Good&quot;,  # Agent is professional, confident, and handles objections effectively.
    8: &quot;Very Good&quot;,  # Agent is persuasive, clear, and builds strong rapport.
    9: &quot;Excellent&quot;  # Agent is highly skilled, engaging, and successfully leads the conversation.
}

Agent Persuasiveness Scale (0-4) = {
  0: &quot;Not Persuasive&quot;,  # Fails to overcome objections, lacks confidence.
  1: &quot;Low Persuasiveness&quot;,  # Struggles but attempts to address concerns.
  2: &quot;Moderate Persuasiveness&quot;,  # Can handle objections but lacks strong influence.
  3: &quot;Highly Persuasive&quot;,  # Overcomes objections well, leads conversation.
  4: &quot;Extremely Persuasive&quot;  # Strongly convinces the client, high success rate.
}

You must return the structured output in JSON format. The keys must remain consistent. Do not add any explanations.

Input:  
An unstructured call transcript where:
- Speaker labels may be missing.
- The conversation may contain grammatical mistakes.
- The flow may be disorganized.

Output Format:
A JSON object with:
- Structured conversation
- Completion status
- Key metadata insights
- Same dictionary keys for consistency

Example Output (JSON Format)

```json
{
  &quot;agent_name&quot;: &quot;Ethan&quot;,
  &quot;permission_confirmation&quot;: 2,
  &quot;client_age&quot;: 80,
  &quot;client_gender&quot;: 1,
  &quot;client_decision_maker&quot;: 1,
  &quot;client_insurance_status&quot;: 1,
  &quot;call_transcript&quot;: [
    {
      &quot;speaker&quot;: &quot;Agent&quot;,
      &quot;text&quot;: &quot;Hello, good morning! This is Ethan. How are you today?&quot;
    },
    {
      &quot;speaker&quot;: &quot;Client&quot;,
      &quot;text&quot;: &quot;I&#x27;m fine.&quot;
    },
    {
      &quot;speaker&quot;: &quot;Agent&quot;,
      &quot;text&quot;: &quot;That’s great! May God bless you. I&#x27;m calling because the state has approved an annual cost final expense program. To check if you qualify, may I ask how old you are?&quot;
    },
    {
      &quot;speaker&quot;: &quot;Client&quot;,
      &quot;text&quot;: &quot;I&#x27;m 80 years old and I already have insurance, but I’m not interested. Thank you.&quot;
    },
    {
      &quot;speaker&quot;: &quot;Agent&quot;,
      &quot;text&quot;: &quot;No problem! I’m not asking you to buy or change your plan. I just want to ensure you&#x27;re aware of updated benefits you might be missing.&quot;
    },
    {
      &quot;speaker&quot;: &quot;Client&quot;,
      &quot;text&quot;: &quot;No, I’m still not interested.&quot;
    },
    {
      &quot;speaker&quot;: &quot;Agent&quot;,
      &quot;text&quot;: &quot;I understand. Just to confirm, at the age of 80, do you make your own financial decisions?&quot;
    },
    {
      &quot;speaker&quot;: &quot;Client&quot;,
      &quot;text&quot;: &quot;Yes, I do.&quot;
    },
    {
      &quot;speaker&quot;: &quot;Agent&quot;,
      &quot;text&quot;: &quot;Alright, I appreciate your time. Have a great day!&quot;
    },
    {
      &quot;speaker&quot;: &quot;Client&quot;,
      &quot;text&quot;: &quot;You too. Goodbye.&quot;
    }
  ],
  &quot;call_completion&quot;: 1,
  &quot;call_outcome&quot;: 0,
  &quot;client_objection&quot;: &quot;I&#x27;m not interested.&quot;,
  &quot;agent_objection_response&quot;: &quot;Explained that it’s not about buying but about updated benefits.&quot;,
  &quot;client_sentiment&quot;: 5,
  &quot;follow_up&quot;: 0,
  &quot;follow_up_type&quot;: 0,
  &quot;agent_performance&quot;: 6,
  &quot;agent_persuasiveness_score&quot;: 2,
  &quot;transfer_success_rate&quot;: 0,
  &quot;call_drop_reason&quot;: 3,
  &quot;do_not_call&quot;: 0,
  &quot;misrepresentation_risk&quot;: 0,
}

Unstructured Transcript:
Speaker A: Hi, good morning, this is Ethan. How are you? Well, what can I do for you, sir? Actually, I&#x27;m calling you informed about that State has approved annual cost final expense program. So just to make you qualify. Yeah, I know. How old are you? What&#x27;s your age, sir? Where are you calling from, sir? Where are you calling from, sir? I&#x27;m calling you from U.S. savings Center. We are located in Austin, Texas. Since that. Why are you calling too early in the morning? People are still sleeping. Do you know what time is it? Sorry to catch your turn on time, sir, but it&#x27;s not taking you much time. I don&#x27;t look like I&#x27;m not calling from Texas.



JSON Output:


**output:** 


{&quot;agent_name&quot;: &quot;Ethan&quot;, &quot;permission_confirmation&quot;: 0, &quot;client_age&quot;: 0, &quot;client_gender&quot;: 2, &quot;client_decision_maker&quot;: 2, &quot;client_insurance_status&quot;: 0, &quot;call_transcript&quot;: [{&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;Hi, good morning. This is Ethan. How are you?&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;Well, what can I do for you, sir?&quot;}, {&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;Actually, I am calling to inform you that the state has approved an annual cost final expense program. To check if you qualify, may I ask your age?&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;Why are you calling so early in the morning? People are still sleeping. Do you know what time it is?&quot;}, {&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;Sorry to catch you at a bad time, sir. It won&#x27;t take much time.&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;I don&#x27;t like that you&#x27;re calling so early.&quot;}], &quot;call_completion&quot;: 0, &quot;call_outcome&quot;: 3, &quot;client_objection&quot;: &quot;Call was made too early in the morning.&quot;, &quot;agent_objection_response&quot;: &quot;Apologized for the early call.&quot;, &quot;client_sentiment&quot;: 0, &quot;follow_up&quot;: 0, &quot;follow_up_type&quot;: 0, &quot;agent_performance&quot;: 3, &quot;agent_persuasiveness_score&quot;: 1, &quot;transfer_success_rate&quot;: 0, &quot;call_drop_reason&quot;: 3, &quot;do_not_call&quot;: 0, &quot;misrepresentation_risk&quot;: 0}
{&quot;agent_name&quot;: &quot;Ethan&quot;, &quot;permission_confirmation&quot;: 2, &quot;client_age&quot;: 0, &quot;client_gender&quot;: 2, &quot;client_decision_maker&quot;: 2, &quot;client_insurance_status&quot;: 0, &quot;call_transcript&quot;: [{&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;Hi, good morning! This is Ethan. How are you?&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;Well, what can I do for you, sir?&quot;}, {&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;Actually, I&#x27;m calling to inform you about the state-approved annual cost final expense program. To see if you qualify, may I ask how old you are?&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;Where are you calling from, sir?&quot;}, {&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;I&#x27;m calling from the U.S. Savings Center. We are located in Austin, Texas.&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;You&#x27;re calling too early in the morning. People are still sleeping. Do you know what time it is?&quot;}, {&quot;speaker&quot;: &quot;Agent&quot;, &quot;text&quot;: &quot;I&#x27;m sorry to catch you at this time, sir, but it won&#x27;t take much of your time.&quot;}, {&quot;speaker&quot;: &quot;Client&quot;, &quot;text&quot;: &quot;I don&#x27;t look like I&#x27;m not calling from Texas.&quot;}], &quot;call_completion&quot;: 0, &quot;call_outcome&quot;: 2, &quot;client_objection&quot;: &quot;You&#x27;re calling too early in the morning.&quot;, &quot;agent_objection_response&quot;: &quot;Apologized for the time and assured it wouldn&#x27;t take much time.&quot;, &quot;client_sentiment&quot;: 2, &quot;follow_up&quot;: 1, &quot;follow_up_type&quot;: 1, &quot;agent_performance&quot;: 4, &quot;agent_persuasiveness_score&quot;: 1, &quot;transfer_success_rate&quot;: 0, &quot;call_drop_reason&quot;: 4, &quot;do_not_call&quot;: 0, &quot;misrepresentation_risk&quot;: 0}