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How To Use The New Response Feedback Feature

Iggy Odighizuwa avatar
Written by Iggy Odighizuwa
Updated over 3 months ago

Overview

This documentation covers how to provide feedback and training data to your Charlie AI setter to improve its conversational intelligence. The system allows for two types of training data:

  1. Disqualification feedback

  2. Response feedback

Benefits

  • Innovative training capability unique to the platform

  • Improved conversational intelligence over time

  • Ability to make feedback local or global across your account

  • Progressive learning and improvement of AI responses

Training Methods

Using the Playground for Response Training

  1. Access the Playground

    • Navigate to your AI setter

    • Go to Settings > Testing Playground

  2. Conduct Test Conversations

    • Start a conversation with your AI setter

    • Observe responses

    • Identify areas for improvement

  3. Provide Response Feedback

    • Click on "Lead Info" after receiving an AI response

    • Select "Give Feedback"

    • Write specific suggestions for improvement

    • Submit feedback

  4. Test Implementation

    • Return to playground

    • Re-trigger the conversation

    • Verify if AI implements the feedback

    • Continue conversation to test sustained improvement

Managing Training Data

  1. Access Knowledge Base

    • Navigate to the knowledge base section

    • Review existing training data

  2. Edit Feedback

    • Select feedback entry

    • Click Edit

    • Update feedback content

    • Set feedback scope (local/global)

    • Activate/deactivate feedback as needed

Best Practices

Training Schedule

  • Dedicate regular time for training (recommended: 15-30 minutes weekly)

  • Choose a consistent day (e.g., every Friday)

  • Test various conversation scenarios

Feedback Quality

  • Focus on specific improvements

  • Include examples of better responses

  • Ensure feedback is clear and actionable

  • Test feedback implementation immediately

Global vs Local Implementation

  • Consider whether feedback should apply to:

    • Single AI setter (local)

    • All AI setters on your account (global)

  • Use global feedback for universal improvements

  • Keep local feedback for specialized use cases

Success Metrics

  • Improved response accuracy

  • Better lead engagement

  • More natural conversation flow

  • Consistent implementation of feedback

  • Enhanced disqualification accuracy

Next Steps

  1. Review current AI setter conversations

  2. Identify areas needing improvement

  3. Create a regular training schedule

  4. Monitor implementation of feedback

  5. Adjust training strategy based on results

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