Understanding Chat Agent Analytics

Agent Analytics helps you evaluate your AI agent’s performance by providing insights into conversations, messages, and customer feedback. You can use this dashboard to monitor activity over a selected period and understand how users are interacting with your agent.

Accessing Agent Analytics

Open Analytics from the left-hand navigation menu. The Analytics dashboard contains several tabs, including Overview, Chats, Help Center, FAQs, and News & Release. Select Chats to access Agent Analytics.

Understanding the Performance Metrics

The Agent Analytics dashboard displays key performance indicators at the top of the page. These include Total Conversations, Total Messages, Messages with Likes, and Messages with Dislikes. Each metric shows its current value alongside a percentage change compared with the previous period.

These indicators help you monitor conversation volume, message activity, and customer feedback. Positive and negative changes provide a quick overview of how performance is shifting over time.

Filtering Analytics by Date

Use the date-range dropdown in the upper-right corner to choose the period you want to analyze. Available options include Last 7 Days, Last 30 Days, Last 90 Days, Last 6 Months, This Month, Last Month, and Custom.

Selecting a different date range updates the dashboard metrics and charts to reflect the chosen period. Use Custom to define a specific timeframe for more focused analysis.

Analyzing Chats and Messages

The Chats & Messages chart displays conversation and message activity over the selected period. The chart uses separate indicators for chats and messages, allowing you to compare their activity and observe changes over time.

Reviewing this chart can help you identify periods of increased or reduced activity and understand how conversation volume relates to message volume.

Reviewing Message Feedback

The Message Likes vs Dislikes chart displays customer feedback on agent messages. Likes and dislikes are represented separately, helping you assess how users respond to the agent’s answers.

Feedback data may not appear until your application has collected relevant interactions. When no feedback data is available, the chart may remain empty while still displaying its legend.

Using Analytics to Evaluate Your Agent

Use Agent Analytics to monitor conversation activity, compare message volume, and review customer feedback across different time periods. Regularly checking these metrics can help you identify performance changes and understand how users experience your AI agent.

Choose a date range that matches your review period and compare the available indicators to make informed decisions about your agent’s performance and support experience.