Conversation volume
Counts are derived from persisted tickets and messages within the selected workspace.
Live support analytics
Support analytics
Illustrative product motion
Conversation demand
Illustrative product view
Support measurement flow
Recorded workspace events become inspectable operational metrics.
System view
Signals in
Analytics Engine
Event aggregation
Outcomes
What breaks
A ticket count alone cannot explain why customers wait, which channel creates demand, or where the knowledge base keeps failing.
The operational change
Volume, response, resolution, channel, and knowledge signals stay connected to the conversations that produced them.
Product view
Illustrative layout of the shipped workflow. Live workspace screens use tenant data and permission checks.
Read the signal, then inspect its evidence
All channels · product workflow
Conversation demand
Illustrative product view · source events retained
Conversation volume
Response time
Knowledge gaps
Signal
Demand changed
Demand is connected to real conversations.
Evidence checked
Capability map
Every surface below maps to a working product state, server action, or provider-backed workflow.
Counts are derived from persisted tickets and messages within the selected workspace.
Operational timing uses real message and ticket state timestamps rather than showcase values.
Website and connected provider conversations remain attributable to their source.
Unanswered patterns and source performance help owners decide what information to improve.
Working sequence
A message becomes a tenant-scoped conversation.
Message and ticket events contribute to operational metrics.
Owners review demand and response patterns.
The team updates knowledge, staffing, or automation.
Explore the operational view without seeded numbers or detached predictions.