Go High Level: Testing Voice AI Agents

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Briefing Doc: Testing Voice AI Agents

Source: Excerpts from "Testing Voice AI Agents: HighLevel Support Portal"

Main Theme: This document provides a practical guide on how to test and optimize the performance of Voice AI agents before deployment.

Key Ideas & Facts:

• Importance of Testing: Testing is crucial to understand how a Voice AI agent handles various inquiries, which helps refine its performance and ultimately increase conversion rates.
• "Before deploying your agent, it’s important to test its functionality. You can learn more about how your AI Agent handles specific inquiries that may arise from a conversation with a prospect or customer, and you can use that information to fine-tune your Voice AI Agent so you ultimately get a higher conversion rate!"
• Conducting Test Calls: The platform provides a straightforward process to simulate real conversations with the AI agent. This involves:

1. Selecting the agent's outgoing caller ID.
2. Entering the user's phone number to receive the test call.
3. Engaging in a natural conversation with the AI agent during the call.

• Reviewing Test Call History: The platform stores detailed data from test calls, enabling comprehensive analysis and improvement. Key data points include:
• Call duration
• Call status (e.g., Completed, Missed)
• Full conversation transcript
• Playback of the call recording
• Summarized insights from the call
• "When you perform a test call, you can have a full conversation with your Voice AI Agent exactly how a customer or prospect would. This will help you understand how the AI Agent sounds on the call, and how they handle call, so you can make any necessary changes to the AI Agent configurations."

Actionable Insights:

• Utilize the testing functionality to gain a realistic understanding of the AI agent's conversational flow and effectiveness.
• Leverage the detailed data from test call history to identify areas needing improvement in the agent's responses and overall performance.
• Regularly test and refine the AI agent based on insights gathered to ensure optimal performance and user experience.

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