Share report
mu.chat/share/insights_7M9Q2
Settings
Read-only view
Weekly report
Conversation report sharing
Share a secure view of chats, messages, leads, tags, conversation summaries, and feedback with sales, support, or leadership.
Muchat turns every conversation into actionable signals: chat and message volume, user type, submitted forms, hot leads, recurring topics, sentiment, and positive or negative feedback.
May 13
Chats
4K
mu.chat/share/insights_7M9Q2
Settings
Read-only view
Weekly report
Share a secure view of chats, messages, leads, tags, conversation summaries, and feedback with sales, support, or leadership.
Understand where each conversation started and which channels, devices, and paths create better leads.
View data for the last 7 days, 30 days, 3 months, year, or any custom range.
Send chats, leads, forms, tags, and summaries to CSV, CRM workflows, or BI tools.
Filter by AI Agent, topic, satisfaction, country, browser, signed-in state, or lead status.
Ask which user segments are unhappy, what topic is repeating, or which channel produces better leads.
Muchat records and groups key chat events, so teams can report how many chats started, leads were captured, and cases reached a human team.
This chart shows monthly recorded event counts, making it easy to compare started chats, captured leads, and human handoffs month by month.
Switch between volume, human handoff pressure, and user sentiment by hour.
Muchat detects user sentiment from chat text, question tone, and feedback signals.
Positive sentiment leads
62%
PositivePositive
Users received a complete answer or showed buying intent.
Neutral
Negative
Detect rising issues, product questions, and purchase objections before they become tickets.
Muchat does more than count events; it shows where the user came from, what they asked, what they needed, and why they are ready for follow-up.
The user lands on pricing with source and page context attached.
They ask about pricing, setup time, limits, and fit.
Muchat tags the topic, sentiment, and purchase readiness.
Contact details are attached to the conversation profile.
A short behavior summary is ready for human follow-up.
Muchat analytics are designed for everyday decisions, not just looking at a few numbers.
See automatic and manual topics together, manage tags, and freeze new topic detection when needed.
Track thumbs up, thumbs down, sentiment, conversation summaries, and chats that need review in one actionable view.
Separate submitted forms, hot leads, anonymous or signed-in users, and conversion paths from the conversation stream.
Join thousands of businesses building AI assistants with Muchat to support customers at any scale, across chat, messaging apps, and voice.

