> ## Documentation Index > Fetch the complete documentation index at: https://ago.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Monitor and Improve Agent Performance > Learn how to use analytics, evaluation, and feedback tools to continuously improve your agents Deploying an agent is just the beginning. AGO's Dashboard, Thread Evaluator, and feedback tools help you spot quality issues and fix them before they affect more users. ## Prerequisites * At least one agent deployed and handling conversations * Admin or Account Manager access The Dashboard gives you a high-level view of how your agents are doing. 1. Navigate to **Dashboard** in the sidebar — the **Overview** tab opens by default 2. Select a time range (e.g., Last 7 days) from the header filters 3. Review the four key metrics at the top: | Metric | What to Watch For | | ---------------------------- | ------------------------------------------------------- | | **Number of Threads** | Is conversation volume growing or declining? | | **Escalation Rate** | Rising rates mean the agent can't handle some questions | | **Positive Evaluation Rate** | Dropping rates signal quality issues | | **Number of Users** | Are new users engaging with the agent? | 4. Compare to the previous period using the +/- percentages. A sudden change is worth investigating. See [Performance Dashboard](/features/performance-dashboard) for all available metrics and tabs. Numbers tell you *what* is happening. Reading conversations tells you *why*. 1. Navigate to **Chat History** in the sidebar 2. Click **More filters** and apply filters to focus your review: * **CX Score Range** = Poor or Needs Improvement — find the worst conversations * **Support Asked** = Yes — see what the agent couldn't handle * **Needs Review** = Yes — conversations flagged by the LLM evaluator 3. Read through 5-10 conversations to understand patterns Look for patterns, not individual failures. If multiple conversations fail on the same topic, that's a knowledge gap. If the agent misunderstands instructions, that's a prompt issue. See [Conversations](/features/conversations-list) for all filtering options. The Thread Evaluator automatically scores every conversation across five quality dimensions. 1. Navigate to **Settings** > **Thread Evaluation** > **Thread Evaluator** 2. Toggle the evaluator on 3. Review the five scoring dimensions and their default weights: | Dimension | Default Weight | What It Measures | | ------------------ | -------------- | ---------------------------------------------------------------- | | Resolution Quality | 25% | Did the agent address the request? | | Response Accuracy | 20% | Were responses consistent and contradiction-free? | | Tone & Empathy | 20% | Did the tone match your agent's guidelines? | | Efficiency | 20% | Was the conversation handled without unnecessary back-and-forth? | | Customer Effort | 15% | How easy was it for the user to get their answer? | 4. Optionally add custom instructions to align scoring with your quality standards 5. Click **Save** Once enabled, conversations are scored daily. Conversations below the minimum thresholds are flagged for review. See [Thread Evaluator](/features/thread-evaluator) for configuration details. After the evaluator has run for a day or two, check the Evaluation tab. 1. Navigate to **Dashboard** and select the **Evaluation** tab 2. Review the **CX Score gauge** — this is your overall quality score (0-100) 3. Check **dimension averages** — which dimension is pulling the score down? 4. Review the **CX Score distribution** — what share of conversations fall into Poor (0-49), Needs Improvement (50-79), and Good (80-100)? 5. If you have multiple agents, check **CX Score by Agent** to compare performance | CX Score Range | Interpretation | | -------------- | ------------------------------------------------------------- | | 80-100 | Good — minor refinements only | | 50-79 | Needs improvement — investigate the lowest dimensions | | 0-49 | Poor — review conversations in this range to find root causes | See [CX Score](/features/cx-score) for how the score is calculated. Direct feedback from users gives you specific signals that automated scoring may miss. 1. Navigate to **Dashboard** and select the **Feedback** tab 2. Review the issue type distribution — which category dominates? 3. Click through to individual conversations to understand the context 4. Navigate to **Feedbacks** in the sidebar for the full list with filtering and reviewer assignment Common patterns and fixes: | Feedback Type | Likely Cause | Fix | | ------------------------- | ------------------------------- | ------------------------------------ | | **Inaccurate** | Outdated or conflicting content | Update the knowledge base | | **Incomplete** | Documents missing detail | Expand existing docs or add new ones | | **Information Not Found** | Topic not covered | Add new documentation | | **Technical Issue** | System error | Check integration configurations | See [Feedback Analytics](/features/feedback-analytics) and [Feedback List](/features/feedback-list). Topic analysis helps you categorize conversations automatically and spot trending subjects. 1. Navigate to **Settings** > **Conversation Labels** and create your topics (see [Conversation Labels](/features/conversation-labels)) 2. Navigate to **Settings** > **Topic Analyzer** and enable it (see [Topic Analyzer](/features/thread-tagger)) 3. After conversations are analyzed, check the **Topics** tab on the Dashboard (see [Topics Analytics](/features/topics-analytics)) The Topics tab shows a treemap of topic distribution, daily trends, and per-agent breakdowns — including CX Score and escalation rate per topic. Use what you've learned to fix issues systematically: 1. **Identify** — use the Dashboard to find the biggest issue (low CX dimension, high escalation, common feedback type) 2. **Diagnose** — read conversations in Chat History to understand the root cause 3. **Fix** — update the knowledge base, agent instructions, or tool configuration 4. **Test** — run [Simulation Testing](/features/simulation-testing) to validate the fix 5. **Deploy** — push the change to production 6. **Monitor** — watch the Dashboard to confirm the metric improves Repeat this cycle weekly. ## Checklist * [ ] Performance Dashboard reviewed * [ ] Low-scoring conversations investigated in Chat History * [ ] Thread Evaluator configured and enabled * [ ] CX Score dimensions analyzed in the Evaluation tab * [ ] User feedback reviewed * [ ] Topics configured and Topic Analyzer enabled * [ ] First improvement cycle completed ## What's Next * [Performance Dashboard](/features/performance-dashboard) - All dashboard tabs and metrics * [Thread Evaluator](/features/thread-evaluator) - Evaluation configuration * [CX Score](/features/cx-score) - Scoring methodology and interpretation * [Simulation Testing](/features/simulation-testing) - Validate changes before deploying * [Agent Best Practices](/guides/agent-best-practices) - Design patterns for better agents