Post Conversation Analytics

Post-Conversation Analytics applies NLP and ML models to call and chat data to surface trends, automate compliance monitoring, and generate conversation summaries. It enables teams to understand underlying sentiment, pinpoint unmet needs, and identify key interests.

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.