- Conversation Intelligence
- The use of AI to analyze customer conversations for intent, sentiment, topics, quality signals, risks, and business insights.
Why CX and AI teams search for this
Teams search for conversation intelligence when they want to turn support conversations into insights for QA, VoC, coaching, product feedback, and operational improvement.
Conversation Intelligence is the use of AI and analytics to extract insight from customer conversations across calls, chats, emails, tickets, and messaging channels. It turns unstructured language into structured signals that CX, QA, sales, product, and operations teams can use.
Conversation intelligence typically identifies: - Customer intent and contact reason - Sentiment and emotion - Topics and emerging themes - Quality and compliance signals - Coaching opportunities - Product feedback and process friction - Revenue, churn, or escalation risk
Why It Matters: Customer conversations contain the most direct evidence of what customers need, where operations break, and how agents or AI systems perform. Conversation intelligence makes that evidence searchable, measurable, and actionable.
Examples
- A CX team finds that delivery complaints increased after a carrier change.
- A QA team identifies agents who need coaching on de-escalation language.
- A product team discovers repeated confusion around a new billing feature.
FAQs
What is conversation intelligence used for in CX?
It is used for Voice of Customer analysis, quality assurance, coaching, issue detection, product feedback, compliance monitoring, and customer journey improvement.
How is conversation intelligence different from call analytics?
Call analytics focuses mainly on voice calls. Conversation intelligence covers voice plus digital channels such as chat, email, tickets, WhatsApp, and messaging.