Agent Analysis

Analyze conversation quality and extract structured data from customer interactions.

Agent analysis provides powerful tools to systematically evaluate conversation performance and extract valuable information from customer interactions. These LLM-powered features help you measure agent effectiveness and gather actionable business insights.

Overview

The Conversational AI platform provides two complementary analysis capabilities:

  • Success Evaluation: Define custom metrics to assess conversation quality, goal achievement, and customer satisfaction
  • Data Collection: Extract specific data points from conversations such as contact information, issue details, or any structured information

Both features process conversation transcripts using advanced language models to provide actionable insights that improve agent performance and business outcomes.

Key Benefits

Track conversation success rates, customer satisfaction, and goal completion across all interactions to identify improvement opportunities.

Capture valuable business information without manual processing, reducing operational overhead and improving data accuracy.

Ensure agents follow required procedures and maintain consistent service quality through systematic evaluation.

Gather structured insights about customer preferences, behavior patterns, and interaction outcomes for strategic decision-making.

Integration with Platform Features

Agent analysis integrates seamlessly with other Conversational AI capabilities:

  • Post-call Webhooks: Receive evaluation results and extracted data via webhooks for integration with external systems
  • Analytics Dashboard: View aggregated performance metrics and trends across all conversations
  • Agent Transfer: Use evaluation criteria to determine when conversations should be escalated

Getting Started

1

Choose your analysis approach

Determine whether you need success evaluation, data collection, or both based on your business objectives.

2

Configure evaluation criteria

Set up Success Evaluation to measure conversation quality and goal achievement.

3

Set up data extraction

Configure Data Collection to capture structured information from conversations.

4

Monitor and optimize

Review results regularly and refine your criteria and extraction rules based on performance data.