> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.droog.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Conversation Analytics

> See how your users interact with your assistant — and use those insights to keep improving it.

## Know what your users are actually asking

Once your assistant is live, real users start asking real questions. Analytics gives you a window into those conversations — so you can understand what's working, what's not, and where to improve.

Droog has two levels of analytics:

* **Workspace Analytics** — a bird's-eye view across all your assistants combined
* **Bot-Level Analytics** — a detailed breakdown for each individual assistant

***

## Workspace Analytics

The Workspace Analytics page gives you a combined view of activity across **all your assistants** in one place. This is the right place to start when you want to understand the overall health of your Droog deployment.

<Frame caption="Workspace Analytics — a combined view of sessions, messages, and performance trends across all your active assistants">
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/droogtechnologies-496fe651/images/analytics-workspace.png" alt="Workspace Analytics Dashboard" />
</Frame>

### How to open it

1. Go to your main **Dashboard**
2. Click **Analytics** in the left navigation

You can filter by date range using the **From** and **To** date pickers, and toggle between **Day** and **Month** views to zoom in or out on trends. Use **Active Bots Only** to filter out inactive assistants from the view.

***

### Summary metrics

The five cards at the top give you an instant health check across your entire workspace:

| Metric              | What it means                                                                                          |
| ------------------- | ------------------------------------------------------------------------------------------------------ |
| **Total Sessions**  | The number of individual conversations started by users across all your assistants                     |
| **Total Messages**  | The total number of messages exchanged — both user questions and assistant replies                     |
| **Avg Latency**     | The average time your assistant takes to reply to a message                                            |
| **P95 Latency**     | The response time for the slowest 5% of messages — useful for spotting occasional delays               |
| **Escalation Rate** | The percentage of conversations where the assistant couldn't fully resolve the user's query on its own |

<Info>
  A high **Escalation Rate** means users are frequently hitting dead ends. This is a strong signal to review your knowledge base and add missing content.
</Info>

***

### Usage & Performance Trends chart

Below the summary cards is a chart that plots **messages**, **sessions**, and **average latency** over your selected date range — all in one view.

<Frame caption="Usage and Performance Trends — messages and sessions shown as bars, average latency as a dashed line, plotted day by day">
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/droogtechnologies-496fe651/images/analytics-trends.png" alt="Usage and Performance Trends Chart" />
</Frame>

Use this chart to spot:

* **Spikes in sessions or messages** — often linked to campaigns, product launches, or events bringing traffic to your site
* **Latency increases** — if the latency line climbs sharply on a particular day, check if large knowledge base changes were made around that time
* **Quiet periods** — consistently low engagement may mean users aren't finding the chat widget easily

***

### Bot Usage Breakdown

At the bottom of the Workspace Analytics page is a table breaking down activity **per assistant** — so you can see which bots are doing the most work.

<Frame caption="Bot Usage Breakdown — per-assistant view showing status, sessions, messages, and storage">
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/droogtechnologies-496fe651/images/analytics-bot-breakdown.png" alt="Bot Usage Breakdown Table" />
</Frame>

| Column           | What it tells you                                       |
| ---------------- | ------------------------------------------------------- |
| **Bot Name**     | The name of the assistant                               |
| **Status**       | Whether the assistant is currently active or inactive   |
| **Sessions**     | Number of conversations started on this assistant       |
| **Messages**     | Total messages exchanged on this assistant              |
| **Storage (MB)** | How much knowledge base storage this assistant is using |

***

## Bot-Level Analytics

For a deeper look at any individual assistant, open that assistant from your dashboard. The overview panel shows detailed metrics for that bot alone — broken into four sections.

<Frame caption="Bot-level analytics — four detail panels covering performance, engagement, feedback, and automation health for one assistant">
  <img src="https://mintlify.s3.us-west-1.amazonaws.com/droogtechnologies-496fe651/images/analytics-bot-detail.png" alt="Bot Analytics Detail Panels" />
</Frame>

***

### Performance & Cost

*How fast the bot responds and what it costs to run.*

This panel tells you about the speed and operational cost of your assistant.

| Metric             | What it means                                                                   |
| ------------------ | ------------------------------------------------------------------------------- |
| **Avg Latency**    | The average time taken to respond to a user message                             |
| **P95 Latency**    | Response time for the slowest 5% of messages — helps identify occasional delays |
| **Cost / Session** | Estimated cost per conversation                                                 |
| **Cost / Message** | Estimated cost per individual message                                           |

<Tip>
  Cost metrics help you understand usage at scale. As your assistant handles more conversations, these numbers help you plan your usage and choose the right plan.
</Tip>

***

### User Engagement

*How actively users interact with the bot.*

This panel shows how users are actually behaving inside conversations.

| Metric                 | What it means                                                                             |
| ---------------------- | ----------------------------------------------------------------------------------------- |
| **Total Users (Est.)** | Estimated number of unique users who have interacted with the assistant                   |
| **Active Users**       | Users who sent at least one message in the selected period                                |
| **Avg Msg / Session**  | Average number of messages per conversation — higher means users are engaging more deeply |
| **Dropoff Rate**       | Percentage of users who opened the chat but didn't send a message                         |

<Info>
  A high **Dropoff Rate** may mean users are unsure what to ask when they open the chat. Consider adding a welcome message or example questions to give users a clear starting point.
</Info>

***

### User Feedback

*How users rate the quality of your assistant's responses.*

Users can rate individual responses with a thumbs up or thumbs down directly inside the chat. This panel aggregates that feedback.

| Metric          | What it means                             |
| --------------- | ----------------------------------------- |
| **Thumbs Up**   | Number of responses users found helpful   |
| **Thumbs Down** | Number of responses users found unhelpful |
| **Avg Rating**  | Overall satisfaction score out of 5       |

<Tip>
  Your **Thumbs Down** responses are your most valuable improvement signal. Browse those specific conversations to find exactly which answers frustrated users — then update the relevant documents in your knowledge base.
</Tip>

***

### Automation Health

*The bot's ability to handle conversations on its own — without needing to escalate.*

| Metric                | What it means                                                                        |
| --------------------- | ------------------------------------------------------------------------------------ |
| **Total Escalations** | Number of conversations where the assistant couldn't resolve the query independently |
| **Escalation Rate**   | Percentage of all conversations that ended in an escalation                          |

A low escalation rate means your assistant is self-sufficient. A high rate is a clear signal that your knowledge base has gaps that need filling.

***

## Using analytics to improve your assistant

Analytics isn't just a report — it's a feedback loop. Here's how to act on what you see:

<CardGroup cols={2}>
  <Card icon="triangle-exclamation" title="High escalation rate?">
    Review conversations that escalated. Identify topics the assistant couldn't answer and upload content to cover those gaps.
  </Card>

  <Card icon="thumbs-down" title="Low feedback scores?">
    Filter for Thumbs Down responses. Find the weak answers and improve the relevant documents in your knowledge base.
  </Card>

  <Card icon="chart-line" title="Latency spikes?">
    Check if latency increases coincide with large knowledge base uploads or high-traffic days. Flag to support if spikes persist.
  </Card>

  <Card icon="user-minus" title="High dropoff rate?">
    Add a friendly opening message or example questions to your assistant to give users a clear starting point.
  </Card>
</CardGroup>

***

## A simple weekly review routine

A 10-minute weekly check is enough to keep your assistant improving consistently.

1. **Open Workspace Analytics** → check total sessions and escalation rate at a glance
2. **Review the trends chart** → spot any unusual spikes or drops in the past week
3. **Open Bot-Level Analytics** for your most active assistant → check feedback scores and dropoff rate
4. **Act on one thing** → upload a missing document, adjust a constraint, or improve the welcome message

Small, consistent improvements compound quickly. An assistant reviewed weekly will be significantly sharper after a month than one left untouched.

***

## What's next?

<CardGroup cols={2}>
  <Card icon="database" href="/guides/managing-knowledge" title="Update your knowledge base">
    Add content to cover the gaps your analytics revealed.
  </Card>

  <Card icon="flask" href="/guides/testing" title="Test your changes">
    After uploading new content, test to confirm the improvements are working.
  </Card>
</CardGroup>

<Note>
  **Have a question?** Reach us at [hi@droog.io](mailto:hi@droog.io)
</Note>
