Signals are spread across the journey.
Teams may need to compare separate views to understand repeat questions, handovers and needs that remain unresolved.
Arabot CX Platform · Conversation Intelligence
Understand the journey behind every conversation.
Bring engagement activity, customer journeys and conversation signals into one view. Find where interactions slow down and which patterns could help your team improve the experience.
Illustrative interface
Conversation overview
Conversation journey
Conversation begins
Journey in progress
Outcome or follow-up
The difference
From scattered signals to a clearer view.
Conversation Intelligence helps teams review patterns across the customer journey and decide where a closer look is needed.
Review the journey in context.
Bring activity, journey patterns and handover context together as a clearer starting point for investigation and improvement.
A capability within Arabot CX Platform
See the patterns shaping the customer journey.
Use conversation data to understand what people ask, where they need help and how service journeys progress.
Performance dashboards
See message activity, response patterns and engagement signals together.
Journey analysis
Follow interaction paths toward their goals and see where people may need help.
Sentiment and themes
Use AI-assisted sentiment and recurring themes to find conversations worth a closer look.
Conversation playback
Replay conversations to review how an interaction unfolded and identify opportunities to improve it.
Reports and data access
Use tagged reports, exports and API access to work with conversation insights in your reporting workflow.
Journey health scoring
Understand experience quality through user needs, handovers, automation and sentiment.
Available capability · built from real user conversations
Customer Journey Health Scoring
Learn from the conversations your customers actually have to understand the quality of their experience. Bring recurring needs, audience patterns and handover context together with indicators of how the conversation journey is working.
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Top user challenges
Find repeat questions, points of friction and needs that remain unmet.
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Main user segments
Recognize the main audience groups and how their needs or interaction patterns differ.
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Handover insights
Examine requests around a transfer and how the human-agent interaction appears to conclude. Identify needs that could return to a safer bot or AI-agent flow, without assuming the issue was resolved.
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Automation rate
The share of conversations completed entirely by the AI agent/ bot, with no transfer to a human agent.
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Sentiment score
Of the conversations analyzed, the percentage in which end-users reported positive sentiment.
From insight to improvement
Turn insight into a considered next step.
A practical review cycle keeps the evidence visible and the decision with the people responsible for the service.
Find the pattern
Notice recurring questions, points of friction and journeys that need a closer look.
Review the context
Compare the interaction with its journey and handover context; keep uncertainty visible.
Choose an improvement
Teams decide what to clarify, automate, route or keep with a person—then review what changes.
Automation opportunities to review
Not every handover should become a bot flow.
Use journey context to help teams distinguish requests that may suit more guided automation from work that should remain human-led.
Potential for guided automation
Repeatable requests and predictable next steps may be worth reviewing for a clearer self-service flow.
Keep human-led
Exceptions and situations that need judgement should remain with the appropriate team.
Illustrative categories only. Teams review evidence and decide what to change; these are not customer findings.
Arabot CX Platform · Conversation Intelligence
Make more sense of the conversations you already have.
See how Conversation Intelligence can support your customer experience goals.