Bot Learns from Conversations by Editing Auto Suggestions

This article will help you understand how to use Bot Learns from The Conversation

I. Introduction

The process of Bot learns from Conversations by Editing Auto Suggestion.

The process by which a bot learns from conversations through editing auto suggestions is a sophisticated feedback loop that enhances the bot's ability to respond accurately over time.

1. Initial Adjustment: The cycle starts when a Customer Service (CS) representative adjusts the auto suggestions in a live chat based on their interactions with customers.

2. Bot Learning: Approximately an hour later, the bot analyzes these conversations and integrates the new insights into its learning system, showcasing what it has learned in a section labeled "Bot Learns From Conversation."

3. Admin Review: An administrator then reviews these new insights to ensure their accuracy and relevance. This step is crucial for maintaining the quality of responses.

4. Knowledge Base Update: Upon approval, the administrator imports the validated information into the bot’s knowledge base.

5. Data Availability: For the bot to utilize this updated information effectively, it must be readily available in its knowledge base.

This continuous learning process allows the bot to refine its auto-suggestions, improving its ability to provide accurate and contextually appropriate responses. By involving both human oversight and automated learning, the system ensures that the bot's knowledge remains up-to-date and reliable.

II. How to use

• To access this feature you can follow: from Dashboard -> Bots -> Bot's Knowledge -> Bot Learns from Conversations.

• There, a tab appears:

the tools to decide which act will be used for each question-answer data.

• 3 features let you decide each Question - Answer Data:

  • Import (): Import the data to the Knowledge Base.
  • Edit (): Edit your data before import to the Knowledge Base
  • Delete (): Delete unwanted data.