Published on 11 October 2022

Driving Actions That Matter in Your Contact Center

Words by:

Annisa Nur Fauzi

Contact center phone conversations are a goldmine of information, with an average conversation consisting of more than a thousand spoken words. By successfully transcribing and analyzing these words, organizations can make informed decisions to lower costs, optimize the customer experience, drive sales, and improve compliance.

But this treasure of information will remain locked unless you can accurately capture the words being said, what they mean, and have the tools to intelligently analyze the data produced. Verint® has released a new transcription engine, powered by Verint Da Vinci AI™ & Analytics. This new engine powers Verint Speech Analytics™, the top-rated speech analytics solution on the market.1 It leverages advanced deep neural network (DNN) models to provide the most accurate transcription and comprehension accuracy available today.2 This breakthrough engine is available as part of Verint Speech Analytics as well as other Verint solutions, such as Verint Automated Quality Monitoring™ and Verint Engagement Data Management™. With this new capability, Verint solutions offer best-in-class accuracy while maintaining superior security and cost effectiveness.

Comprehension Accuracy

Comprehension accuracy is the ability to understand the meaning and intent of a call, including relevant topics and sentiment. Verint Da Vinci AI and Analytics provides unparalleled comprehension accuracy through sophisticated semantic intelligence and machine learning. In fact, we have found that organizations generally achieve over 90 percent comprehension accuracy with Verint Speech Analytics.

So how does it work?

Taking analytics beyond the basics of identifying and trending words and phrases, the Verint solution capitalizes on semantic intelligence to provide a deeper understanding of the meaning and context behind the words used in conversations, along with resulting behaviors and actions. It can automatically determine the connection between spoken terms and phrases to identify the relationship and significance between them. By clustering these topics and relationships, users can gain a broader picture of emerging trends and themes, and in a single click, transform them into meaningful categories, vastly accelerating speed to insight. Using machine learning, the solution offers further value through its ability to “self-train” as new topics are added, and proactively identifies and emerges rapidly surfacing conversations for analysis. Natural language processing is applied to extract the automated themes and relations, which are then used to enrich out-of-thebox ontology and create new categories, continually enhancing insights.

Be Alerted Before Disaster

When a new problem arises in your contact center, every second matters. If a sudden issue such as a website problem, product outage, or weather event occurs, customer sentiment can plummet in an instant. It’s not enough to simply track this data — you need to take prompt action. With Verint, alerts can notify the appropriate employees when certain thresholds are reached with customer sentiment, interaction category volumes, agent sentiment, and much more. This early notification saves precious minutes, reducing the time and effort from insight to action.

inutes, reducing the time and effort from insight to action.

Seeing the Big Picture Verint Interaction

Analytics is essential for seeing the full picture of your customer insight and sentiment. The out-of-the-box dashboards provide the high-level information that executives need to make critical decisions, and proactive notifications trigger immediate action to keep operations running efficiently and effectively.

Gain Easy Access to Data

Because the solution communicates insights derived from the unified, comprehensive capabilities of Verint Speech Analytics™ and Verint Text Analytics™, your organization has easy access to the data needed, in one location, to quickly spot issues and resolve them, across customer channels.

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