Speech and text analytics overview

Speech and text analytics is a set of features that provide an automated analysis of an interaction’s content, to provide deep insight into customer-agent conversations. Speech and text analytics provides the automated transcription of  interactions and subsequently turns them into readable and searchable text. Along with sentiment analysis, speech and text analytics creates meaning from otherwise unstructured data.

Organizations can use this data to fulfill key use cases around agent performance improvement (for example, decrease AHT, increase FCR, sales conversion, and so on), compliance, customer satisfaction (for example, NPS), and customer business intelligence.  

Key features

  • Voice transcription – Get insight into conversations between external (customer) and internal (IVR, ACD, agent, conference or voicemail) participants to see who is saying what. This information can be used to improve employee training and feedback, and to identify business problems. For more information, see About voice transcription
  • Sentiment analysis Recognize a customer’s attitude during an interaction based on the language used during an interaction. By capturing the sentiment of the customer’s phrases, users gain valuable insight into the customer’s experience and subsequently use this information to improve service delivery. For more information, see About sentiment analysis.  
  • Interaction overview – A visual representation of the interaction that includes a variety of information and controls (play, pause, annotate, live monitoring, adjust volume and speed, sentiment and topic markers, so on), that enable agents and supervisors to review, recognize and determine customer sentiment and agent competency. For more information, see About the interaction overview
  • Programs, topics and phrases – Boost the recognition of a business issue by instructing your system to search for, recognize, and classify specific phrases. For more information, see About programs, topics, and phrases.