How to Track ElevenLabs Voice Agent Quality in Galileo ( Tutorial)
Most businesses using ElevenLabs voice agents only see basic performance metrics. Discover how Galileo provides rich, actionable insights into your agent's effectiveness - including completion rates, efficiency scores, and turn-by-turn conversation analysis.
Why Galileo Matters for Voice Agents
Most businesses deploying ElevenLabs voice agents struggle with a critical blind spot: they can see basic performance data, but lack deep insights into how effectively their agents are actually solving user problems. Without proper analytics, you're flying blind - unable to identify why certain conversations fail or how to systematically improve your agent's performance.
Galileo solves this by providing rich, actionable metrics that go far beyond ElevenLabs' native analytics. Instead of just knowing your agent had a conversation, you'll understand exactly how well it performed at each turn - with specific rationales explaining both successes and failures.
Voice agents without proper analytics are like customer service reps working in the dark: They might sound professional, but you have no way to measure if they're actually solving problems effectively or just creating frustration.
Key Metrics You'll Get in Galileo
Galileo provides several critical metrics that transform how you understand your voice agent's performance:
- Completion Rate: Measures how thoroughly your agent fulfilled the user's request (not just whether it responded)
- Efficiency Score: Evaluates how quickly and directly the agent resolved the user's need
- Turn-by-Turn Analysis: Scores each exchange in the conversation for completeness and correctness
- Rationale Scoring: Explains why specific interactions received poor scores, highlighting improvement areas
In the tutorial video at 2:15, you can see how Galileo evaluates a sample conversation where the agent scored poorly on completion - it responded to the user but didn't fully address their request about attracting Facebook users to Instagram.
Turn-by-Turn Conversation Analysis
Galileo's most powerful feature is its ability to analyze each exchange in your voice agent conversations. Where ElevenLabs might show you the conversation transcript, Galileo scores each turn on multiple dimensions and provides specific rationales.
For example, in the demo conversation (visible at 3:30 in the video), Galileo identifies exactly where the agent failed to provide a complete answer about attracting Facebook users. The system doesn't just say "this was bad" - it explains why the response was incomplete and suggests what a better answer might include.
This granular analysis is impossible with ElevenLabs alone: You'd know conversations happened, but not why some succeeded while others failed - making systematic improvement nearly impossible.
Simple Implementation Process
Setting up Galileo tracking for your ElevenLabs voice agent requires just a few key components:
- Session Handlers: Code to start and end conversation sessions in Galileo
- Turn Tracking: Logging when the agent speaks and when the human speaks
- Metadata: Optional additional context about the conversation's purpose
As shown in the example repository (referenced at 1:45 in the video), the implementation is straightforward. The handlers automatically log interactions to Galileo where they're processed into rich metrics - no manual analysis required.
Leveraging Historical Conversation Data
One of Galileo's most valuable features is its ability to aggregate and analyze historical conversations. Where ElevenLabs might show you recent activity, Galileo lets you filter all past sessions by various metrics to identify patterns.
You can quickly find all conversations where your agent scored poorly on completeness or efficiency, then analyze them to identify systemic issues rather than isolated incidents. This historical perspective (demonstrated at 4:10 in the video) is crucial for making data-driven improvements to your voice agent's performance.
Watch the Full Tutorial
See the complete implementation and Galileo dashboard in action. At 2:45 in the video, you'll see how Galileo evaluates a real conversation with an ElevenLabs voice agent, providing specific scores and rationales for each turn.
Key Takeaways
Monitoring your ElevenLabs voice agents with Galileo provides transformative insights that basic analytics can't match. You'll move from guessing why conversations succeed or fail to having concrete data and specific improvement recommendations.
In summary: Galileo turns voice agent monitoring from a black box into a transparent, data-driven process where every conversation provides actionable insights for continuous improvement.
Frequently Asked Questions
Common questions about voice agent analytics
Galileo provides comprehensive metrics including completion rates (how well the agent fulfilled user requests), efficiency scores (how quickly it resolved issues), and turn-by-turn conversation analysis.
You can see metrics like completeness of responses and get rationales for why certain interactions scored poorly. These go far beyond the basic analytics available in ElevenLabs' native dashboard.
- Completion Rate: Measures whether the agent fully addressed the user's request
- Efficiency Score: Evaluates how directly the agent solved the problem
- Turn Analysis: Scores each exchange in the conversation individually
Galileo tracks conversations by logging each session (a composition of multiple traces) where it records when the agent speaks and when the human speaks.
The system automatically calculates metrics as the conversation progresses, allowing you to analyze performance at both the session level and individual turn level. This happens through simple handlers that mark the start and end of conversations.
- Sessions are composed of multiple interaction traces
- Each speaker turn is logged with timestamps
- Metrics calculate automatically as the conversation progresses
While ElevenLabs provides basic performance information, Galileo offers richer, more actionable metrics that actually help you improve your voice agent.
You get detailed scores on agent effectiveness, can filter sessions by performance metrics, and receive specific rationales explaining why certain interactions succeeded or failed. This enables targeted improvements rather than guesswork.
- Deeper insight into why conversations succeed or fail
- Actionable rationales for performance scores
- Ability to filter and compare multiple sessions
The setup is straightforward and requires minimal code changes to your existing ElevenLabs implementation.
You just need handlers for starting conversations, sessions, and ending sessions. These handlers log the interactions between your voice agent and users to Galileo automatically. The example repository shows how simple this implementation can be.
- Requires only a few additional handlers
- Minimal changes to existing code
- Example implementation available for reference
Yes, Galileo stores all your historical conversations with rich metadata and performance metrics.
You can filter past sessions by various metrics to identify patterns - like when your agent consistently underperformed in completeness or efficiency. This historical analysis helps identify systemic issues rather than just isolated incidents.
- All past conversations are stored with full metrics
- Filter by date range, performance scores, or other criteria
- Identify patterns across multiple interactions
Beyond basic performance metrics, Galileo helps you understand why certain conversations succeeded or failed at a granular level.
You can see exactly where in the conversation flow your agent struggled, get rationales for poor performance scores, and identify specific areas needing improvement in your agent's logic or training. This transforms improvement from guesswork to data-driven decisions.
- Identify specific failure points in conversations
- Understand why certain responses scored poorly
- Pinpoint training or logic gaps in your agent
Metrics appear in Galileo's dashboard as the conversation progresses, giving you near real-time visibility.
You can monitor active sessions and see metrics calculating turn-by-turn. However, some deeper analysis (like comparing multiple sessions or calculating aggregate scores) may require the conversation to complete for full scoring and comparison.
- Turn-by-turn metrics update in near real-time
- Session-level metrics complete when conversation ends
- Historical comparisons require completed sessions
GrowwStacks specializes in implementing advanced monitoring and analytics for voice AI agents like those built with ElevenLabs.
We can integrate Galileo with your existing voice agent setup, create custom dashboards tailored to your business metrics, and help optimize your agent's performance based on the rich data Galileo provides. Our team handles the technical implementation so you can focus on improving your customer experience.
- Free consultation to assess your monitoring needs
- Seamless Galileo integration with your ElevenLabs agent
- Custom dashboards highlighting your key metrics
Ready to Transform Your Voice Agent Analytics?
Don't settle for guessing why conversations succeed or fail. With Galileo integration, you'll have concrete data to systematically improve your ElevenLabs voice agent's performance. GrowwStacks can have your monitoring dashboard live in days.