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Analytics & Monitoring

Track workspace performance, usage patterns, and costs

Analytics & Monitoring

Monitor workspace performance, track usage, and understand costs with built-in analytics dashboards.

Accessing Analytics

Navigate to workspace → Analytics tab

You'll see an overview dashboard with key metrics and charts.

Key Metrics (KPI Cards)

Total Conversations

  • Number of unique conversations started
  • Includes all agents in workspace
  • Resets based on date filter

Total Messages

  • Total messages exchanged (user + agent)
  • User messages + AI responses
  • Shows engagement level

Total Tokens Used

  • Combined input + output tokens
  • Varies by model and conversation length
  • Used for cost calculation

Total Spend (If credits enabled)

  • Total credits spent on AI usage
  • Includes platform markup + your markup
  • Hidden if requireCredits = false

Credits Remaining (If credits enabled)

  • Current workspace credit balance
  • Color-coded: Green (healthy), Yellow (low), Red (empty)
  • Hidden if requireCredits = false

Usage Trends Chart

Line chart showing usage over time:

  • Messages - Daily message volume (blue line)
  • Tokens - Daily token usage (green line)
  • Cost - Daily spending (orange line, if credits enabled)

Use to:

  • Spot usage spikes or drops
  • Identify busy/quiet periods
  • Forecast future usage

Date filters: Last 7 days, 30 days, 90 days, All time

Agent Performance Table

Shows per-agent breakdown:

ColumnDescription
Agent NameName of the agent
ConversationsNumber of conversations
MessagesTotal messages sent
Avg. Tokens/MsgAverage tokens per message
Total CostTotal spent (if credits enabled)

Use to:

  • Identify most-used agents
  • Find inefficient agents (high tokens/msg)
  • Allocate resources based on usage

Cost by Agent Chart (If credits enabled)

Bar chart showing spend per agent:

  • Each bar = one agent
  • Height = total cost
  • Sorted by highest spend first

Use to:

  • Identify expensive agents
  • Optimize model selection for high-cost agents
  • Budget planning

Hidden when requireCredits = false.

Date Filtering

All analytics support date range filtering:

Quick filters:

  • Last 7 days (default)
  • Last 30 days
  • Last 90 days
  • All time

Custom range:

  • Click date picker
  • Select start and end date
  • Apply filter

All charts and metrics update automatically.

Understanding the Data

What Counts as a Conversation?

A conversation is a unique thread between a user and agent:

  • Starts with first user message
  • Continues until session ends (30 min inactivity)
  • New session = new conversation

How Are Tokens Calculated?

Tokens are units of text:

  • ~1 token = 4 characters (English)
  • Input tokens: User message + system instructions + conversation history
  • Output tokens: Agent's response

Example:

  • User: "What are your hours?" (5 tokens)
  • System instructions: 100 tokens
  • History: 50 tokens
  • Agent response: "We're open 9-5 Mon-Fri" (8 tokens)
  • Total: 163 tokens (155 input, 8 output)

How Are Costs Calculated?

Cost depends on:

  1. Tokens used (input + output)
  2. Model pricing (varies per model)
  3. Platform markup (20% default)
  4. Your markup (if workspace credits enabled)

See Credits & Billing for detailed examples.

Monitoring Best Practices

Daily checks:

  • Glance at KPI cards for anomalies
  • Check Credits Remaining (if enabled)
  • Verify no service interruptions

Weekly reviews:

  • Review Usage Trends for patterns
  • Check Agent Performance for outliers
  • Identify optimization opportunities

Monthly analysis:

  • Compare month-over-month growth
  • Review cost trends
  • Adjust pricing/models if needed

Common Insights

High Token/Message Ratio

What it means: Agent is verbose or processing large context

Solutions:

  • Reduce conversation history limit
  • Shorten system instructions
  • Use more concise model (gpt-4o-mini)

Sudden Usage Spike

What it means: New user traffic or viral content

Actions:

  • Check credit balance
  • Review agent is handling load well
  • Consider scaling up if sustained

Low Conversation Count

What it means: Low adoption or poor discoverability

Solutions:

  • Promote agent more
  • Improve agent placement/visibility
  • Review agent's usefulness for users

Cost Growing Faster Than Usage

What it means: Users asking longer questions or agent using expensive model

Actions:

  • Review recent conversations
  • Consider cheaper model
  • Optimize system instructions

Exporting Data

Currently, analytics are view-only in dashboard.

For exports:

  • Use API (coming soon)
  • Contact support for CSV export
  • Take screenshots for reports

Privacy & Data Retention

What's stored:

  • Message content (user + agent)
  • Conversation metadata (timestamps, agent, model)
  • Usage metrics (tokens, costs)

How long:

  • Conversations: 90 days (configurable)
  • Analytics summaries: Forever
  • Transaction history: Forever

Who can see:

  • Admin - All analytics including costs
  • Editor - All analytics including costs (if no credits)
  • Viewer - All analytics except costs

Troubleshooting

Analytics not updating?

  • Refresh page
  • Check date filter isn't too narrow
  • Wait 5 minutes (some metrics batched)

Missing data?

  • Verify agent has had usage
  • Check correct workspace selected
  • Ensure date range includes activity

Costs seem wrong?

  • Review transaction history for details
  • Verify model pricing hasn't changed
  • Check markup percentages in settings

Next Steps

Congratulations! You've completed the Getting Started guide.

Next recommended reads:

  1. Deployment - Share agents with end users
  2. Best Practices - Optimize performance and costs
  3. API Reference - Integrate programmatically

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