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🎥 Refer to the setup video for a step-by-step visual guide:

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Overview

The Analytics feature provides powerful insights into how your chatbot is performing. It helps you track conversations, measure engagement, analyze chat quality, and understand user behavior through interactive graphs and key performance metrics. This guide explains how to view analytics data, apply date filters, export reports, and interpret analytics sections.

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Accessing Analytics

1

Open the Dashboard

  • Log in to your dashboard
  • Navigate to Logs and Tracking from the main menu
  • Click on Analytics in the left sidebar
2

View Analytics Data

  • The Analytics page loads with charts and performance metrics
  • By default, data is shown for Today
Analytics Dashboard

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Analytics Interface Overview

The Analytics dashboard is organized into multiple sections to give a complete view of chatbot performance.

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Date Range Filters

Use the date selector at the top of the page to filter analytics data.
  • Quick Date Filters
  • Custom Range

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Exporting Analytics Data

You can export analytics data for reporting or further analysis.

Export to CSV

Download analytics data in CSV format for spreadsheets and reports.

Export as JSON

Export raw analytics data in JSON format for technical analysis or integrations.

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Analytics Sections

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Overview Metrics

The Overview section displays key performance indicators at a glance.
  • Total Sessions: Total number of chat conversations during the selected time period.
  • Total Messages: Total number of messages exchanged between users and the chatbot.
  • Message Credits Used: Number of message credits consumed in the selected time range.
  • Avg. Messages per Session: Average number of messages in each chat session.

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Message Activity

The Message Activity graph shows message volume over time.
  • Message count trends
  • Peak usage times
  • Daily or hourly activity patterns
Helps you understand user engagement and chatbot usage patterns.

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Session Activity

The Session Activity graph tracks chatbot sessions over time.
  • Number of chat sessions
  • Growth or decline in usage
  • Engagement trends
Indicates how often users start conversations with your chatbot.

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Chat Quality Distribution

This section classifies conversations based on quality.

Good Chats

Conversations with positive engagement or successful outcomes.

Neutral Chats

Conversations with average or mixed engagement.

Bad Chats

Conversations where the chatbot may not have met user expectations.

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Best Practices

  • Monitor analytics regularly to track chatbot performance
  • Use message and session trends to identify peak usage
  • Review chat quality to improve responses and training
  • Export data for deeper analysis and reporting

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Next Steps

Human Support

View and manage human support requests

Live Chat

Manage live chat sessions and provide real-time support