Positive_Feedback

The “Positive_Feedback” tracker detects instances where customers voice approval, satisfaction, gratitude, or compliments. By capturing these positive mentions, teams gain insights into what works well, reinforcing successful strategies and encouraging agents to continue delivering high-quality service.

Who Benefits:

• Project Managers & Team Leads: Recognize effective practices and behaviors that garner positive feedback, informing coaching and training.
• Sales & CX Teams: Understand what aspects of service or product delight customers, guiding enhancements and personalized approaches.
• Business Managers & Strategists: Identify patterns in positive mentions to highlight strong product features or successful marketing efforts.
• Compliance Officers: Ensure that positive feedback is acknowledged and not misrepresented, maintaining trust and transparency.

Value Proposition:

• Confidence & Morale: Highlighting positive feedback boosts representative morale and confirms effective methodologies.
• Data-Driven Recognition: Structured JSON output can inform dashboards for performance reviews, rewards, and motivational programs.
• Continuous Improvement: Insight into what customers appreciate helps refine processes, product features, and support materials.

Data Dictionary

Objective:

Detect phrases that indicate positive sentiment, compliments, or recognition of value. The tracker returns occurrences of matched phrases, along with timestamps and confidence. This data helps teams celebrate successes and reinforce best practices.

Proposed JSON Schema:

{
  "trackers": [
    {
      "name": "Positive_Feedback",
      "matches": [
        {
          "text": "<string>",
          "timestamp": "<ISO 8601 or relative time>",
          "confidence": <number> // 0.0 to 1.0
        }
      ]
    }
  ]
}

Data Dictionary:

If No Matches Found:
If no positive feedback is detected, return an empty matches array for "Positive_Feedback" or omit the tracker. If no trackers match at all, return:

{
  "trackers": []
}

Determining Confidence & Thresholds

How the Positive_Feedback Tracker Works:

• Seed the tracker with phrases representing customer satisfaction or compliments (e.g., "great service," "very helpful," "love this feature," "thank you so much").
• The system interprets these phrases and identifies semantically similar statements that convey approval or appreciation.
• Confidence indicates how closely the detected phrase aligns with positive feedback.

Confidence & Calibration:

• Initial Testing: Validate on known calls to ensure detected phrases accurately represent positive sentiment.
• Refine Phrases: Add or remove seed phrases as you learn which terms customers commonly use to express satisfaction.
• Thresholding: Downstream users can ignore low-confidence matches if needed.
• Stakeholder Feedback: Involve CX leads or product managers to refine definitions and ensure relevant positive mentions are captured.

Prompt Construction & Instructions

Role Specification & Reiteration:

• Present the system as a “highly experienced assistant” identifying positive feedback.
• Reiterate instructions: return only JSON, follow schema, no extra commentary.

No Hallucination:

• Only detect positive feedback if supported by transcript evidence.
• If uncertain, assign a lower confidence or omit matches.

Strict Formatting:

• Return only JSON with trackers.
• If none found, return empty trackers.

Example Prompt for Implementation

System Message (Role: System):
"You are a highly experienced assistant that identifies 'Positive_Feedback' mentions in a conversation. You have:

• A transcript
• A 'Positive_Feedback' tracker defined by seed phrases indicating satisfaction or compliments.

Your task:

1. Detect phrases where the customer expresses approval, gratitude, or positive sentiment.
2. Return text, timestamp, and confidence.
3. Return only JSON as defined. No extra commentary.

Instructions & Variables (example):

{
  "tracker": {
    "name": "Positive_Feedback",
    "phrases": [
      "thank you, this helps",
      "great service",
      "very satisfied",
      "love this feature",
      "you've been very helpful"
    ]
  }
}

User Message (Role: User):
"Analyze the following transcript and detect 'Positive_Feedback' mentions:

[TRANSCRIPT_JSON][TRANSCRIPT_JSON]"

Expected Output Format:

{
  "trackers": [
    {
      "name": "Positive_Feedback",
      "matches": [
        {
          "text": "Your assistance was really helpful, thank you!",
          "timestamp": "2024-07-10T12:40:00Z",
          "confidence": 0.9
        }
      ]
    }
  ]
}