> For the complete documentation index, see [llms.txt](https://help.botpenguin.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.botpenguin.com/analytics/analytics/live-chat-analytics.md).

# Live Chat Analytics

The Live Chat Analytics section helps you track, measure, and improve the performance of your human-assisted chat conversations.

## Live Chat Analytics

The **Live Chat Analytics** section helps you track, measure, and improve the performance of your human-assisted chat conversations. These insights enable teams to understand response efficiency, customer engagement, and overall resolution quality.

{% embed url="<https://youtu.be/GAmnuoNXXYE>" %}

***

### Accessing Live Chat Analytics

Go to: **Analytics → Live Chat**

You can filter data using:

* **Date range**
* **Bots** (specific chatbots)
* **Team** (support agents or teams)
* **Time grouping** (Daily)

***

### Metrics Explained

#### 1. Total Live Chat Sessions

**What it shows:**\
The total number of live chat conversations initiated by users during the selected time period.

**Why it matters:**\
Helps measure chat demand and overall customer engagement with live support.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2FSXk45tEp0S6hLM328XBs%2Fimage.png?alt=media&amp;token=c36ca2ae-6a0e-4e4e-8ec5-42d8cbaa5f4f" alt=""><figcaption></figcaption></figure>

***

#### 2. Live Chat Acceptance Rate

**What it shows:**\
The percentage of incoming live chat requests that were accepted by agents.

**Why it matters:**\
A high acceptance rate indicates good team availability and responsiveness.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2Ffvzy7ajtaeBj0r6Nk05m%2Fimage.png?alt=media&amp;token=204951f0-51a3-49e2-8385-39c39eb0d70b" alt=""><figcaption></figcaption></figure>

***

#### 3. First Response Time

**What it shows:**\
The average time taken by an agent to send the first reply after a chat is assigned.

**Why it matters:**\
Lower first response time improves customer satisfaction and reduces abandonment.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2F03wrPdF30PWcgqDwZaZ4%2Fimage.png?alt=media&amp;token=46da5a63-14c5-4965-92fa-452b0e93d400" alt=""><figcaption></figcaption></figure>

***

#### 4. Average Response Time

**What it shows:**\
The average time taken by agents to respond to user messages throughout the conversation.

**Why it matters:**\
Indicates how actively agents engage during an ongoing chat.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2FufexS1eOOd9d6hZDk9mT%2Fimage.png?alt=media&amp;token=f73cd01a-20c7-4ccb-91ad-1868de4cbacc" alt=""><figcaption></figcaption></figure>

***

#### 5. Average Chat Duration

**What it shows:**\
The average length of a live chat session from start to end.

**Why it matters:**\
Helps understand chat complexity and agent efficiency.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2FqaUDzuXRt8yghM9Oyjs0%2Fimage.png?alt=media&amp;token=cef0889a-7ddc-46ce-bcae-6ff78f764227" alt=""><figcaption></figcaption></figure>

***

#### 6. Resolution Time

**What it shows:**\
The average time taken to fully resolve a chat issue.

**Why it matters:**\
Shorter resolution times reflect effective issue handling.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2F3yy43KIEKyEnxcdb1SEJ%2Fimage.png?alt=media&amp;token=1bdd15fe-36b2-4933-9b67-397d1341c455" alt=""><figcaption></figcaption></figure>

***

#### 7. Chat Abandonment Rate

**What it shows:**\
The percentage of chats where users left before the issue was resolved.

**Why it matters:**\
A high abandonment rate may indicate slow responses or long wait times.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2FgLre4DSDBmv9f4alzU1E%2Fimage.png?alt=media&amp;token=fb13bb04-8a51-4ac1-bca3-fd3b0943701d" alt=""><figcaption></figcaption></figure>

***

#### 8. Chat Resolution Rate

**What it shows:**\
The percentage of chats that were successfully resolved by agents.

**Why it matters:**\
A higher resolution rate means better customer support outcomes.

**Filter Charts:**

Users can filter the data according to the selected bot , their teams, by any selected date period, monthly, weekly or Daily.

<figure><img src="https://1745791824-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAPDb8cKQtGlIAfgHjcsQ%2Fuploads%2FaqHImf0aLZ0LAypgVbjU%2Fimage.png?alt=media&amp;token=34e30f92-21df-446f-80ea-1ef71855856a" alt=""><figcaption></figcaption></figure>