Verint

Analyzes customer phone conversations in real-time to extract sentiment, emotional tone, and customer satisfaction signals. Uses AI to process speech data and identify emotional patterns during live calls.

Automatically identifies and categorizes customer intents from conversations across channels. Uses NLP to understand what customers are trying to accomplish and classify interactions by type.

Manages and optimizes knowledge base content used for automated responses and agent assistance. Identifies gaps in knowledge coverage and suggests content improvements based on customer interactions.

Provides real-time suggestions and guidance to agents during customer interactions. Offers next-best-action recommendations, relevant knowledge articles, and conversation guidance.

Analyzes customer feedback from surveys, reviews, and interactions to identify sentiment trends and emerging issues. Tracks satisfaction metrics over time and identifies root causes of dissatisfaction.

Automatically scores interactions based on quality criteria and generates compliance reports. Provides detailed metrics on adherence to standards, policies, and regulatory requirements.

Scans customer interactions for compliance violations, regulatory risks, and policy breaches in real-time. Identifies problematic language, unauthorized disclosures, or non-compliant agent behavior.

Automatically routes incoming customer inquiries across phone, chat, email, and social channels to appropriate agents or teams based on skills, availability, and priority. Intelligently queues and prioritizes conversations.

Generates suggested or fully automated responses to customer inquiries based on conversation context and knowledge bases. Can provide agent recommendations or send automated replies.

Analyzes agent interactions to identify coaching opportunities, performance gaps, and quality issues. Provides actionable feedback based on actual conversation data and performance metrics.

Predicts customer contact volume and agent staffing needs using historical data and AI models. Optimizes agent schedules to match predicted demand while minimizing labor costs.

Predicts customer satisfaction scores and Net Promoter Score (NPS) based on interaction data and conversation characteristics. Identifies factors that drive satisfaction or dissatisfaction.

Analyzes customer conversations in multiple languages and provides translation capabilities. Enables sentiment, intent, and compliance analysis across global customer bases.

Consolidates customer interaction data from all channels into a unified customer profile and interaction history. Provides 360-degree customer view across phone, chat, email, and social.