📉Analytics
The Analytics page provides detailed insights into your chatbot's performance, customer interactions, response quality, and user engagement.
How to Access Analytics
To open the Analytics page:
Log in to your Wonderchat dashboard.
From the left-side navigation menu, click Analytics.
Select the chatbot you want to analyze (or choose All Chatbots).
Use the date picker or one of the quick date filters to view analytics for a specific time period.
Overview
Overall Customer Satisfaction
Displays customer satisfaction based on feedback collected after conversations.
Metrics
Average Score
Shows the average satisfaction rating received during the selected period.
Ratings range from dissatisfied to very satisfied.
Satisfaction Distribution The colored bar shows the percentage of users in each satisfaction category:
😍 Very Satisfied
😊 Satisfied
😐 Neutral
🙁 Dissatisfied
😭 Very Dissatisfied
This widget helps monitor overall customer sentiment.
Resolution Rate
Shows how effectively your chatbot resolves customer conversations without requiring additional assistance.
Metrics
Overall Resolution Rate
Percentage of chats successfully resolved.
Resolved Chats
Total number of conversations marked as resolved.
Number of Chat Messages
Displays the total number of chat messages exchanged over time.
Purpose
This graph helps identify:
Usage trends
Peak traffic days
Seasonal fluctuations
Changes after updates or new content
Confidence Level
Shows the AI confidence score for chatbot responses.
When confidence tracking is unavailable, the widget displays:
Confidence metrics help determine how certain the AI was when generating responses.
Usage Metrics
Number of Chat Sessions
Displays the total number of chatbot conversations started during the selected period.
A session begins when a visitor starts interacting with the chatbot.
Unique Visitors
Shows the number of individual visitors who interacted with the chatbot.
Each visitor is counted only once regardless of how many conversations they initiate.
Widget Engagements
Measures how many times users interacted with the chatbot widget.
Examples include:
Opening the widget
Clicking suggested questions
This metric indicates how attractive and visible your chatbot is to website visitors.
Conversation Quality
Good Chats
Displays the number of conversations that received positive feedback.
This metric helps identify successful customer interactions.
Bad Chats
Displays the number of conversations that received negative feedback.
A high number may indicate:
Missing knowledge
Incorrect answers
Poor conversation quality
Review these conversations to improve chatbot performance.
Response Speed
Measures how quickly the chatbot responds to users.
Two response metrics are displayed:
TTFT (Time To First Token)
Measures how long it takes before the chatbot starts generating a response.
Lower TTFT results in a more responsive user experience.
Full Response
Measures the total time required to generate the complete responses.
For both TTFT and Full Response, the following statistics are shown:
AVG
Average response time
P50
Median response time
P90
90% of responses are faster than this value
P99
99% of responses are faster than this value
These metrics help identify slow responses and monitor system performance.
Geography
Chats by Location
Displays where chatbot conversations originated.
Countries are ranked by total number of chats.
This helps identify:
Primary customer markets
Geographic trends
Regional adoption
Channels
Chats by Channel
Shows the distribution of conversations across available communication channels.
Example channels include:
Web App
Web Call
This helps understand where customers prefer interacting with the chatbot.
Escalations
Number of Escalated Chats
Displays the number of conversations that were transferred from the chatbot to a human agent.
Escalations may occur when:
The chatbot cannot answer the question.
A human handover is requested.
Business rules require agent intervention.
Monitoring escalations helps identify knowledge gaps.
Average Chat Duration
Shows the average time users spend in chatbot conversations.
Longer conversations may indicate:
Complex support requests
High engagement
Shorter conversations may indicate:
Quick issue resolution
Users leaving early
This metric should be evaluated alongside customer satisfaction.
Sessions by Message Count
Displays the number of sessions grouped by how many messages were exchanged.
Example:
1
User sent only one message
2
Two-message conversations
3
Three-message conversations
4
Four-message conversations
5+
Longer conversations
This chart helps understand conversation depth and engagement.
Most Visited Links
Lists the links shared most frequently by the chatbot.
For each link, the following information is shown:
URL
Number of clicks
An additional summary displays:
Total clicks across all links
Use this report to determine which resources customers access most often.
The Export as CSV button allows downloading the complete report.
Top Questions from Users
Shows the questions most frequently asked by users.
For each question, the report displays:
Question text
Number of times it was asked
This report is useful for:
Identifying common customer needs
Discovering missing knowledge
Improving chatbot training
Creating FAQs
Optimizing documentation
The Export as CSV button downloads the full list for further analysis.
Best Practices
Monitor Customer Satisfaction and Resolution Rate regularly to evaluate chatbot quality.
Review Bad Chats and Escalated Chats to identify areas where the chatbot needs additional training.
Use Top Questions to expand your knowledge base and FAQ content.
Track Response Speed to ensure users receive timely answers.
Analyze Chats by Location and Chats by Channel to understand your audience and optimize deployment strategies.
Export reports periodically for historical tracking and business reporting.
This documentation provides a complete overview of the Analytics page and how each metric can be used to measure and improve chatbot performance.
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