Human + AI: How Augmented Analytics Can Empower Agents, Not Replace Them

The rise of artificial intelligence in customer service has sparked a common misconception — that AI will eventually replace human agents. In reality, the most powerful contact centers are built…

The Link Between AI Call Analytics and Higher Customer Satisfaction Scores (CSAT)

Customer Satisfaction (CSAT) scores are one of the most critical metrics for measuring the success of a contact center. They reflect how well an organization meets customer expectations and directly…

How AI Helps Align Contact Center KPIs with Business Goals

Contact centers play a critical role in driving business outcomes, from customer satisfaction to revenue generation. However, many organizations struggle to connect operational metrics—such as call handling time, first-call resolution,…

5 Ways AI Call Analytics Reduces Agent Burnout and Improves Retention

Contact centers are often high-pressure environments where agents handle a constant stream of customer interactions, manage complex issues, and meet strict performance metrics. This can lead to agent burnout—a critical…

Boosting Agent Productivity with AI Call Summaries and Automated QA

Introduction: The Productivity Challenge in Contact Centers Contact center agents face constant pressure to handle high call volumes, maintain quality interactions, and comply with regulatory requirements. Traditional monitoring methods—manual QA…

Protecting Vulnerable Customers: Ethical Debt Collection with AI Insights

Introduction: The Need for Compassion in Debt Recovery Debt collection has always been a sensitive area for both businesses and customers. While organizations need to recover outstanding balances, vulnerable customers…

Why Sentiment Analysis Alone Isn’t Enough: Real Value in Contact Center AI

Introduction: The Limits of Sentiment-Only Insights For years, sentiment analysis has been one of the most talked-about tools in contact center AI. By detecting whether a customer is happy, frustrated,…

Why Sentiment Analysis Isn’t Enough (and What Features Really Drive Value)

In today’s contact centers, understanding customer emotions is critical for delivering exceptional experiences. Sentiment analysis—detecting positive, neutral, or negative emotions in calls—has become a popular tool for evaluating interactions. However,…

The Human + AI Model: Empowering Agents with Smarter Call Analytics

Contact centers are evolving rapidly, and the expectations for both agents and customers have never been higher. Traditional approaches—manual call monitoring, limited sample-based quality assurance, and delayed feedback—often fail to…

Using AI to Detect Patient Frustration and Improve First Call Resolution

In healthcare, patient experience is critical for satisfaction, adherence, and trust. Call centers serve as the primary point of contact for scheduling, inquiries, and support. However, patient frustration is common…