Post Conversation Analytics

Conversation Analytics uses AI to automatically generate actionable insights from customer conversations. It enables teams to understand underlying sentiment, pinpoint unmet needs, and identify key interests.

Core Analytical Features
The solution provides several key analysis dimensions, available via API or directly within the platform for agents, supervisors, and QA evaluators:

Sentiment & Emotion Analysis: Classifies interactions as Positive, Negative, or Neutral based on language and tone, and detects underlying customer emotions.
Automated Alerting: Flags critical issues in real-time, such as profanity or compliance risks.
Comprehensive Summaries: Generates concise overviews of customer interactions.
Live Transcripts: Provides verbatim records of conversations.
Trend Highlighting: Identifies emerging topics and widespread issues across conversations.

Cross-Functional Applications
These structured insights drive action across the organization:

Contact Centers: Supervisors monitor agent performance and provide targeted coaching, while QA teams filter conversations for evaluation, leading to improved customer satisfaction (CSAT) scores.
Marketing: Gauges real-time customer reactions to campaigns and products.
Tech Support: Identifies and resolves common technical issues promptly.
Business Strategy: Aligns company goals with evolving customer interests and trends.

Proactive Engagement
The analytics can also trigger automated workflows within Conversation Studio, such as alerting a supervisor to a negative interaction or scheduling a callback, enabling proactive customer engagement.