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Analytics

Understand how your AI performs - track conversations, usage and costs, and platform events from one place to optimize and forecast with confidence.

ChatBotKit Analytics gives you a clear view of how your AI is performing, what it is consuming, and what is happening across your account. Instead of guessing, you can see real numbers for conversations, messages, token usage, and system events, then act on them to improve quality and control cost.

Analytics spans three complementary areas - performance, usage, and events - that together turn raw activity into insight you can use to optimize and forecast.

What You Can Do

  • Track performance: See insights across bots, conversations, and messages to understand engagement and quality. See Performance Analytics.
  • Understand usage and cost: Get a detailed token breakdown with input/output ratios and resources linked to the bots and datasets that consume them. See Usage Analytics.
  • Monitor events: Watch system and skillset events in real time for visibility and troubleshooting. See Event Monitoring.
  • Forecast and budget: Use usage trends to predict spend and plan capacity.
  • Find what to fix: Identify resource-intensive components and conversations that need attention.

How It Works

Performance analytics aggregate activity across your bots, conversations, and messages into platform insights. Usage accounting records each interaction with a detailed token breakdown, shows the ratios applied, and links usage directly to the resources that produced it, so cost is traceable. Event monitoring captures system and skillset events as they happen, giving you a live picture of what your AI is doing. All three are available from your dashboard.

Getting Started

Open the dashboard to explore performance insights, usage reports, and event logs. Use usage breakdowns to find your most resource-intensive bots and datasets, and pair analytics with Usage Policies to turn what you learn into automatic guardrails.

Practical Uses

Analytics supports both optimization and governance: improve bots based on real conversation data, forecast and control token spend, identify the components driving cost, and troubleshoot issues quickly through event visibility. It is the feedback loop that helps your AI get better and more efficient over time.

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