# Analytics

> Track conversation volume, message mix, and response times.

URL: https://docs.reaktly.com/docs/platform/analytics

The dashboard's overview answers how much is happening and how the load splits between the AI and your team.

## What the overview shows

| Metric | Meaning |
|---|---|
| **Active conversations** | Conversations in progress now — broken down by AI-handled and human-agent-handled |
| **Conversations** | Sessions started, for today, this week, and this month |
| **Total messages** | Message volume, split into visitor messages and AI messages |
| **Average messages per conversation** | How deep exchanges go — a proxy for whether questions get resolved |
| **Average response time** | How quickly visitors get an answer |
| **Average session duration** | How long conversations run |
| **Peak hours** | When your visitors actually show up — useful for staffing a human presence |

## Reading the numbers

- **A falling messages-per-conversation with stable volume** usually means answers land on the first try.
- **A rising human-agent share** points at a content gap: the AI is handing more over. Check [Conversations](/docs/platform/conversations) for what those visitors asked.
- **Peak hours** are the cheapest lever for takeover coverage — staff the two or three busiest hours before adding people anywhere else.

## A weekly routine

1. Compare conversation volume week over week — growth or seasonality, not day-to-day noise.
2. Look at the AI/human split; investigate the conversations that escalated.
3. Check response time against your own service promise.
4. Feed what you learn back into the knowledge base ([Knowledge base management](/docs/platform/knowledge-base)).