Analytics helps you understand how your AI agent is performing over time. It shows usage, engagement, speed, and reach in a clear and simple way.

This page focuses on patterns and trends, not individual conversations. If you want to review or fix specific chats, use the Activity section instead.

What Analytics Is Used For

Analytics answers questions like:

How many people are using AI?
Where are conversations coming from?
How fast does the AI respond?
Are users giving positive feedback?
Which days are most active?

Analytics helps teams:

Track adoption
Review performance
Share reports with managers or leadership
Make informed decisions over time

Data Availability

Analytics data may not update instantly.

You may see a notice that says:

“Analytics data for today might be delayed.”

This means:

Recent conversations may take some time to appear
Older data is already complete and accurate

This delay helps ensure reliable reporting.

Date Range Selection

At the top of the Analytics page, you can select a date range.

Choose a start date
Choose an end date

All metrics and charts update based on this range

Use date ranges to:

Compare weeks or months
Review performance after changes
Create reports for a specific period

Downloading Analytics Reports

You can download analytics data at any time.

Available formats:

PDF: best for sharing and presentations
JSON: best for developers or integrations
Excel (xlsx): best for spreadsheets and analysis

Downloads always follow:

Selected date range
Current filters

Summary Metrics

These numbers give a quick overview of performance.

Total Conversations

Number of chat sessions started
One conversation may include many messages

Total Messages

Total number of messages exchanged
Includes both user messages and AI responses

Thumbs Up

Count of positive feedback
Shows how many users liked the response

Thumbs Down

Count of negative feedback
Shows where users were not satisfied

Positive Rate

Percentage of positive feedback
Calculated from thumbs up and thumbs down

Average Response Time

Average time the AI takes to reply
Measured in seconds

These metrics help you check overall health at a glance.

Chat Trends

Chats Started

This section shows:

How many chats are started each day
Changes in activity over time

Use this to:

Spot growth or drop in usage
Identify busy or quiet periods
Understand adoption patterns

Chats by Country

This section shows where users are located.

It may include:

A table with country names
Number of messages or chats per country

If no data is available, you may see:

“No data available.”

This can happen when:

Location data is not captured
Usage is very limited

Chats by Channel

This section shows where conversations happen.

Examples of channels:

Playground
Website embed
WhatsApp
Slack
Telegram

Displayed as:

A Pie chart
Percentage and message count per channel

This helps you understand:

Which channels are active
Whether the AI is still in testing or live use
Where adoption is growing

Analytics Insights

The Insights panel highlights key signals automatically.

Peak Activity Day

Shows the most active day
Includes message count for that day

This helps identify:

Usage spikes
High-demand periods

Engagement Rate

Based on feedback activity
Shows how interactive sessions are

A low rate may mean:

Users are not giving feedback
Conversations are short or unclear

Average Response Time

Shown again as a performance signal
Reinforces speed as a quality indicator

Consistent high response time may need attention.

Geographic Reach

Number of countries where chats happened
Shows how widely the AI is used

Helpful for:

Global teams
Regional rollouts
Market expansion tracking

Footer Totals

At the bottom of the Analytics Insights, you may see:

Total Conversations
Total Messages

These numbers reinforce:

Overall usage scale
Activity within the selected date range

What Analytics Does Not Do

Analytics does not:

Show full chat conversations
Allow editing or fixing answers
Retrain the AI
Replace Activity logs

For those tasks, use the Activity section.

How to Use Analytics Effectively

Best practices:

Review analytics weekly or monthly
Watch trends, not single numbers
Combine analytics with Activity reviews
Use exports for reports and reviews
Track changes after training or deployment

Analytics works best when used regularly.

Summary

Analytics helps you:

Measure usage
Track performance
Understand adoption
Share clear reports

It gives a big-picture view of how your AI agent performs over time. For detailed fixes and improvements, use Analytics with the Activity section cooperatively.

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